From 47733dc7a6fc40b21baf6f111538921fe1113e9a Mon Sep 17 00:00:00 2001 From: Pei-Yun Sun Date: Fri, 16 Oct 2020 22:58:49 +1100 Subject: [PATCH] implement multi-faces detections --- .DS_Store | Bin 0 -> 14340 bytes deepface/DeepFace.py | 516 ++++++++-------- deepface/commons/functions.py | 1093 +++++++++++++++++---------------- my_deepface.ipynb | 441 +++++++++++++ test_imgs/.DS_Store | Bin 0 -> 6148 bytes test_imgs/test1.jpg | Bin 0 -> 291396 bytes test_imgs/test2.jpeg | Bin 0 -> 3895 bytes test_imgs/test3.jpg | Bin 0 -> 29904 bytes 8 files changed, 1261 insertions(+), 789 deletions(-) create mode 100644 .DS_Store create mode 100644 my_deepface.ipynb create mode 100644 test_imgs/.DS_Store create mode 100644 test_imgs/test1.jpg create mode 100644 test_imgs/test2.jpeg create mode 100644 test_imgs/test3.jpg diff --git a/.DS_Store b/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..b7e35ea77b6751eb76ce1f968d232573c8d7b1d0 GIT binary patch literal 14340 zcmeHNYitx%6h5c4bS8jIp*&_0SZH{c(k&EPd2QR}Q62%=mX?QXXLqLUgx#I8Gur~S zrY1fTBlw6!1H@=he<1Qpqa?=oj)9=WV3ZhsU}F4XqGBM?KgM%sX1lZ9Ek1q-n0u4C z=gypS=AQe_H+$!vy#RoXX*B>)4FCciOiE*^dJMqNq^B@FJMzjXx`K2ppo7{HfCfF# z2@1rh_1C3{OqhQ$9RjH2DB(>m!oFB}1m07rl$ zz!BgG{Bs1@+)G6m<49g}1ULd5fguFg?}MKXCWEdVbfo>$K^6OiXL|MtZx?FQI>5f> zcV*C(gO0Ra$;Wmj>A0f1#6ZWLuKSre$)GC-9qG6OI_`jO&*-jD(C(f5{I)q@(2>06 z2yg`Q5h$li1=ikb-rBp6T~Bu)95WI<_H9Sob>6*t!>MH4NOqByy}HGqQ+B|BWW3Ac zI}xvWb>6lAs*YvnU!}Ewu09)IA$?9<6NBUmB3P7NFsY7E1PSN@GumhNxEX~D(Vn<& zTGiEGW6`MMlF_AtC<@{@@quu+(HFK9D{VF^sXgp$yJB@m-FAy%#E05Sbf>QMMWpg3 zBWWpmQcKy+x~h@M-Znj{8hwpMI;ooWeZr2y?kFPp`uhV*>#8gLHA`y-D*gR|n)>=m ze_fzG8p|W07 z=`BIDH5D^uc@NVxr8KHlL9j2+n=gwkCXGT;T*J!6qS&&ZxFMMo0t-A)Bg(CDC91_G zRdn2zuMp+7UT3J%X7}RCRifNZFJFR&XqI86dpX!3%llZ*TNKmU)}tjUs?VrT-ekB{IHd>Ws@XYmA{#xwW^p2fHE9Xy90;m3Fpzr=5y2#Yf8-|C!a zYP?FVLi9F!-B-P6Um@c9)^FGtx-G=LGS*@1#PUfqD&{Y)S+S~N=&25Sj$T69EOKaK z((0jZK=rCiVJ;Y zsR+_2$9Rbt5QwT$iKAU6E*FW+Qn9107gq|zS!uMRT_XlX_PR;noX_!vL_xxlm^dO2 zUxw3g4nBeN#J{iLDtre&!*2*U8YP>1KAeWraW2lo1-K9^u@;vT3+r(uhHxEjz>UPj zFt*@MY{Ol|#F)**Zajb~v@lJK9K?r-kB{QxE+e1AWB4MT8pglo4D%d`XA1MrJE0vL zobU=uW{+fz!BgGa0EC4cK`xx{a*}Kv>w*M%K0R?k$Tjt^L`Mp|KHtDm?7VU zk^LMfr1yRd6czo#hF+TK7rG%0QE%^*S=^s*;f>+PKvm|WWY~SYk&JBRjmOPdmQXyp zy$?ajjiqc6#p2O=<2ZV8)=w@LITl$o3R~p%-$5PF9twr_Pv|*)M|M1s)p+~;AUrgF z*Uvldd~HsD5xc*=eh>|7;54g(JWb;0SO8I0APA0wqq6)olOY zx{>$)-wi|IF>(Yr0{;>LEDnW3jpUs9SAF<>*j_t79UXKqoA>Eph1#|YRrYo~lJ<5y tI$_)K>TDyoB3+O*Ne()aT2yYsM!^5oZU?^p&+fl*wjA)i4u5B_!=Jb`BuW4P literal 0 HcmV?d00001 diff --git a/deepface/DeepFace.py b/deepface/DeepFace.py index 8c51d07..d219613 100644 --- a/deepface/DeepFace.py +++ b/deepface/DeepFace.py @@ -33,21 +33,21 @@ def verify(img1_path, img2_path = '', model_name ='VGG-Face', distance_metric = img_list = [[img1_path, img2_path]] #------------------------------ - + resp_objects = [] - + if model_name == 'Ensemble': print("Ensemble learning enabled") - + import lightgbm as lgb #lightgbm==2.3.1 - + if model == None: model = {} - + model_pbar = tqdm(range(0, 4), desc='Face recognition models') - + for index in model_pbar: - + if index == 0: model_pbar.set_description("Loading VGG-Face") model["VGG-Face"] = VGGFace.loadModel() @@ -60,55 +60,55 @@ def verify(img1_path, img2_path = '', model_name ='VGG-Face', distance_metric = elif index == 3: model_pbar.set_description("Loading Facebook DeepFace") model["DeepFace"] = FbDeepFace.loadModel() - + #-------------------------- #validate model dictionary because it might be passed from input as pre-trained - + found_models = [] for key, value in model.items(): found_models.append(key) - + if ('VGG-Face' in found_models) and ('Facenet' in found_models) and ('OpenFace' in found_models) and ('DeepFace' in found_models): print("Ensemble learning will be applied for ", found_models," models") else: raise ValueError("You would like to apply ensemble learning and pass pre-built models but models must contain [VGG-Face, Facenet, OpenFace, DeepFace] but you passed "+found_models) - + #-------------------------- - + model_names = ["VGG-Face", "Facenet", "OpenFace", "DeepFace"] metrics = ["cosine", "euclidean", "euclidean_l2"] - + pbar = tqdm(range(0,len(img_list)), desc='Verification') - + #for instance in img_list: for index in pbar: instance = img_list[index] - + if type(instance) == list and len(instance) >= 2: img1_path = instance[0] img2_path = instance[1] - + ensemble_features = []; ensemble_features_string = "[" - + for i in model_names: custom_model = model[i] - + #input_shape = custom_model.layers[0].input_shape[1:3] #my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue. - + input_shape = custom_model.layers[0].input_shape - + if type(input_shape) == list: input_shape = input_shape[0][1:3] else: input_shape = input_shape[1:3] - - - img1 = functions.preprocess_face(img = img1_path, target_size = input_shape, enforce_detection = enforce_detection, detector_backend = detector_backend) - img2 = functions.preprocess_face(img = img2_path, target_size = input_shape, enforce_detection = enforce_detection, detector_backend = detector_backend) - + + + img1 = functions.preprocess_face(img = img1_path, target_size = input_shape, enforce_detection = enforce_detection, detector_backend = detector_backend)['processed'] + img2 = functions.preprocess_face(img = img2_path, target_size = input_shape, enforce_detection = enforce_detection, detector_backend = detector_backend)['processed'] + img1_representation = custom_model.predict(img1)[0,:] img2_representation = custom_model.predict(img2)[0,:] - + for j in metrics: if j == 'cosine': distance = dst.findCosineDistance(img1_representation, img2_representation) @@ -116,49 +116,49 @@ def verify(img1_path, img2_path = '', model_name ='VGG-Face', distance_metric = distance = dst.findEuclideanDistance(img1_representation, img2_representation) elif j == 'euclidean_l2': distance = dst.findEuclideanDistance(dst.l2_normalize(img1_representation), dst.l2_normalize(img2_representation)) - + if i == 'OpenFace' and j == 'euclidean': #this returns same with OpenFace - euclidean_l2 continue else: - + ensemble_features.append(distance) - + if len(ensemble_features) > 1: ensemble_features_string += ", " ensemble_features_string += str(distance) - + #print("ensemble_features: ", ensemble_features) ensemble_features_string += "]" - + #------------------------------- #find deepface path - + home = str(Path.home()) - + if os.path.isfile(home+'/.deepface/weights/face-recognition-ensemble-model.txt') != True: print("face-recognition-ensemble-model.txt will be downloaded...") url = 'https://raw.githubusercontent.com/serengil/deepface/master/deepface/models/face-recognition-ensemble-model.txt' output = home+'/.deepface/weights/face-recognition-ensemble-model.txt' gdown.download(url, output, quiet=False) - + ensemble_model_path = home+'/.deepface/weights/face-recognition-ensemble-model.txt' - + #print(ensemble_model_path) - + #------------------------------- - + deepface_ensemble = lgb.Booster(model_file = ensemble_model_path) - + prediction = deepface_ensemble.predict(np.expand_dims(np.array(ensemble_features), axis=0))[0] - + verified = np.argmax(prediction) == 1 if verified: identified = "true" else: identified = "false" - + score = prediction[np.argmax(prediction)] - + #print("verified: ", verified,", score: ", score) - + resp_obj = "{" resp_obj += "\"verified\": "+identified resp_obj += ", \"score\": "+str(score) @@ -166,18 +166,18 @@ def verify(img1_path, img2_path = '', model_name ='VGG-Face', distance_metric = resp_obj += ", \"model\": [\"VGG-Face\", \"Facenet\", \"OpenFace\", \"DeepFace\"]" resp_obj += ", \"similarity_metric\": [\"cosine\", \"euclidean\", \"euclidean_l2\"]" resp_obj += "}" - + #print(resp_obj) - + resp_obj = json.loads(resp_obj) #string to json - + if bulkProcess == True: resp_objects.append(resp_obj) else: return resp_obj - + #------------------------------- - + if bulkProcess == True: resp_obj = "{" @@ -191,13 +191,13 @@ def verify(img1_path, img2_path = '', model_name ='VGG-Face', distance_metric = resp_obj += "}" resp_obj = json.loads(resp_obj) return resp_obj - + return None - + #ensemble learning block end #-------------------------------- #ensemble learning disabled - + if model == None: if model_name == 'VGG-Face': print("Using VGG-Face model backend and", distance_metric,"distance.") @@ -214,11 +214,11 @@ def verify(img1_path, img2_path = '', model_name ='VGG-Face', distance_metric = elif model_name == 'DeepFace': print("Using FB DeepFace model backend", distance_metric,"distance.") model = FbDeepFace.loadModel() - + elif model_name == 'DeepID': print("Using DeepID2 model backend", distance_metric,"distance.") model = DeepID.loadModel() - + elif model_name == 'Dlib': print("Using Dlib ResNet model backend", distance_metric,"distance.") from deepface.basemodels.DlibResNet import DlibResNet #this is not a must because it is very huge. @@ -232,18 +232,18 @@ def verify(img1_path, img2_path = '', model_name ='VGG-Face', distance_metric = #------------------------------ #face recognition models have different size of inputs #my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue. - + if model_name == 'Dlib': #this is not a regular keras model input_shape = (150, 150, 3) - + else: #keras based models input_shape = model.layers[0].input_shape - + if type(input_shape) == list: input_shape = input_shape[0][1:3] else: input_shape = input_shape[1:3] - + input_shape_x = input_shape[0] input_shape_y = input_shape[1] @@ -253,17 +253,17 @@ def verify(img1_path, img2_path = '', model_name ='VGG-Face', distance_metric = threshold = functions.findThreshold(model_name, distance_metric) #------------------------------ - + #calling deepface in a for loop causes lots of progress bars. this prevents it. disable_option = False if len(img_list) > 1 else True - + pbar = tqdm(range(0,len(img_list)), desc='Verification', disable = disable_option) - + #for instance in img_list: for index in pbar: - + instance = img_list[index] - + if type(instance) == list and len(instance) >= 2: img1_path = instance[0] img2_path = instance[1] @@ -271,8 +271,8 @@ def verify(img1_path, img2_path = '', model_name ='VGG-Face', distance_metric = #---------------------- #crop and align faces - img1 = functions.preprocess_face(img=img1_path, target_size=(input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend) - img2 = functions.preprocess_face(img=img2_path, target_size=(input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend) + img1 = functions.preprocess_face(img=img1_path, target_size=(input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend)['processed'] + img2 = functions.preprocess_face(img=img2_path, target_size=(input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend)['processed'] #---------------------- #find embeddings @@ -358,7 +358,8 @@ def analyze(img_path, actions = [], models = {}, enforce_detection = True, detec #if a specific target is not passed, then find them all if len(actions) == 0: - actions= ['emotion', 'age', 'gender', 'race'] + # actions= ['emotion', 'age', 'gender', 'race'] + actions = ['emotion', 'age', 'gender'] #print("Actions to do: ", actions) @@ -394,178 +395,175 @@ def analyze(img_path, actions = [], models = {}, enforce_detection = True, detec #--------------------------------- resp_objects = [] - + disable_option = False if len(img_paths) > 1 else True - + global_pbar = tqdm(range(0,len(img_paths)), desc='Analyzing', disable = disable_option) - + #for img_path in img_paths: for j in global_pbar: img_path = img_paths[j] - resp_obj = "{" - disable_option = False if len(actions) > 1 else True pbar = tqdm(range(0,len(actions)), desc='Finding actions', disable = disable_option) - action_idx = 0 - img_224 = None # Set to prevent re-detection - #for action in actions: - for index in pbar: - action = actions[index] - pbar.set_description("Action: %s" % (action)) + # preprocess images + emotion_imgs = functions.preprocess_face(img=img_path, target_size=(48, 48), grayscale=True, enforce_detection=enforce_detection, detector_backend=detector_backend)['processed'] + imgs_224 = functions.preprocess_face(img_path, target_size=(224, 224), grayscale=False, enforce_detection=enforce_detection) # just emotion model expects grayscale images + orig_faces = imgs_224['original'] + imgs_224 = imgs_224['processed'] - if action_idx > 0: - resp_obj += ", " + for i in range(len(imgs_224)): - if action == 'emotion': - emotion_labels = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'] - img = functions.preprocess_face(img = img_path, target_size = (48, 48), grayscale = True, enforce_detection = enforce_detection, detector_backend = detector_backend) + resp_obj = "{" + action_idx = 0 - emotion_predictions = emotion_model.predict(img)[0,:] + #for action in actions: + for index in pbar: + action = actions[index] + pbar.set_description("Action: %s" % (action)) - sum_of_predictions = emotion_predictions.sum() + if action_idx > 0: + resp_obj += ", " - emotion_obj = "\"emotion\": {" - for i in range(0, len(emotion_labels)): - emotion_label = emotion_labels[i] - emotion_prediction = 100 * emotion_predictions[i] / sum_of_predictions + if action == 'emotion': + emotion_labels = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'] - if i > 0: emotion_obj += ", " + emotion_predictions = emotion_model.predict(emotion_imgs[i])[0,:] - emotion_obj += "\"%s\": %s" % (emotion_label, emotion_prediction) + sum_of_predictions = emotion_predictions.sum() - emotion_obj += "}" + emotion_obj = "\"emotion\": {" + for i in range(0, len(emotion_labels)): + emotion_label = emotion_labels[i] + emotion_prediction = 100 * emotion_predictions[i] / sum_of_predictions - emotion_obj += ", \"dominant_emotion\": \"%s\"" % (emotion_labels[np.argmax(emotion_predictions)]) + if i > 0: emotion_obj += ", " - resp_obj += emotion_obj + emotion_obj += "\"%s\": %s" % (emotion_label, emotion_prediction) - elif action == 'age': - if img_224 is None: - img_224 = functions.preprocess_face(img_path, target_size = (224, 224), grayscale = False, enforce_detection = enforce_detection) #just emotion model expects grayscale images - #print("age prediction") - age_predictions = age_model.predict(img_224)[0,:] - apparent_age = Age.findApparentAge(age_predictions) + emotion_obj += "}" - resp_obj += "\"age\": %s" % (apparent_age) + emotion_obj += ", \"dominant_emotion\": \"%s\"" % (emotion_labels[np.argmax(emotion_predictions)]) - elif action == 'gender': - if img_224 is None: - img_224 = functions.preprocess_face(img = img_path, target_size = (224, 224), grayscale = False, enforce_detection = enforce_detection, detector_backend = detector_backend) #just emotion model expects grayscale images - #print("gender prediction") + resp_obj += emotion_obj - gender_prediction = gender_model.predict(img_224)[0,:] + elif action == 'age': + #print("age prediction") + age_predictions = age_model.predict(imgs_224[i])[0,:] + apparent_age = Age.findApparentAge(age_predictions) - if np.argmax(gender_prediction) == 0: - gender = "Woman" - elif np.argmax(gender_prediction) == 1: - gender = "Man" + resp_obj += "\"age\": %s" % (apparent_age) - resp_obj += "\"gender\": \"%s\"" % (gender) + elif action == 'gender': + #print("gender prediction") - elif action == 'race': - if img_224 is None: - img_224 = functions.preprocess_face(img = img_path, target_size = (224, 224), grayscale = False, enforce_detection = enforce_detection, detector_backend = detector_backend) #just emotion model expects grayscale images - race_predictions = race_model.predict(img_224)[0,:] - race_labels = ['asian', 'indian', 'black', 'white', 'middle eastern', 'latino hispanic'] + gender_prediction = gender_model.predict(imgs_224[i])[0,:] - sum_of_predictions = race_predictions.sum() + if np.argmax(gender_prediction) == 0: + gender = "Woman" + elif np.argmax(gender_prediction) == 1: + gender = "Man" - race_obj = "\"race\": {" - for i in range(0, len(race_labels)): - race_label = race_labels[i] - race_prediction = 100 * race_predictions[i] / sum_of_predictions + resp_obj += "\"gender\": \"%s\"" % (gender) - if i > 0: race_obj += ", " + elif action == 'race': + race_predictions = race_model.predict(imgs_224[i])[0,:] + race_labels = ['asian', 'indian', 'black', 'white', 'middle eastern', 'latino hispanic'] - race_obj += "\"%s\": %s" % (race_label, race_prediction) + sum_of_predictions = race_predictions.sum() - race_obj += "}" - race_obj += ", \"dominant_race\": \"%s\"" % (race_labels[np.argmax(race_predictions)]) + race_obj = "\"race\": {" + for i in range(0, len(race_labels)): + race_label = race_labels[i] + race_prediction = 100 * race_predictions[i] / sum_of_predictions - resp_obj += race_obj + if i > 0: race_obj += ", " - action_idx = action_idx + 1 + race_obj += "\"%s\": %s" % (race_label, race_prediction) - resp_obj += "}" + race_obj += "}" + race_obj += ", \"dominant_race\": \"%s\"" % (race_labels[np.argmax(race_predictions)]) - resp_obj = json.loads(resp_obj) + resp_obj += race_obj + + action_idx = action_idx + 1 + + resp_obj += "}" + + resp_obj = json.loads(resp_obj) - if bulkProcess == True: resp_objects.append(resp_obj) - else: - return resp_obj - if bulkProcess == True: - resp_obj = "{" + # resp_obj = "{" + # + # for i in range(0, len(resp_objects)): + # resp_item = json.dumps(resp_objects[i]) + # + # if i > 0: + # resp_obj += ", " + # + # resp_obj += "\"instance_"+str(i+1)+"\": "+resp_item + # resp_obj += "}" + # resp_obj = json.loads(resp_obj) + # return resp_obj + return resp_objects, orig_faces - for i in range(0, len(resp_objects)): - resp_item = json.dumps(resp_objects[i]) - - if i > 0: - resp_obj += ", " - - resp_obj += "\"instance_"+str(i+1)+"\": "+resp_item - resp_obj += "}" - resp_obj = json.loads(resp_obj) - return resp_obj - #return resp_objects - - -def detectFace(img_path, detector_backend = 'opencv'): - img = functions.preprocess_face(img = img_path, detector_backend = detector_backend)[0] #preprocess_face returns (1, 224, 224, 3) - return img[:, :, ::-1] #bgr to rgb +def detectFace(img_path, detector_backend='opencv'): + imgs = functions.preprocess_face(img=img_path, detector_backend=detector_backend)['processed'] #preprocess_face returns (1, 224, 224, 3) + for i in range(len(imgs)): + imgs[i] = imgs[i][0][:, :, ::-1] #bgr to rgb + return imgs def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine', model = None, enforce_detection = True, detector_backend = 'opencv'): - + model_names = ['VGG-Face', 'Facenet', 'OpenFace', 'DeepFace'] metric_names = ['cosine', 'euclidean', 'euclidean_l2'] - + tic = time.time() - + if type(img_path) == list: bulkProcess = True img_paths = img_path.copy() else: bulkProcess = False img_paths = [img_path] - + if os.path.isdir(db_path) == True: - + #--------------------------------------- - + if model == None: if model_name == 'VGG-Face': - print("Using VGG-Face model backend and", distance_metric,"distance.") + print("Using VGG-Face model backend and", distance_metric, "distance.") model = VGGFace.loadModel() elif model_name == 'OpenFace': - print("Using OpenFace model backend", distance_metric,"distance.") + print("Using OpenFace model backend", distance_metric, "distance.") model = OpenFace.loadModel() elif model_name == 'Facenet': - print("Using Facenet model backend", distance_metric,"distance.") + print("Using Facenet model backend", distance_metric, "distance.") model = Facenet.loadModel() elif model_name == 'DeepFace': - print("Using FB DeepFace model backend", distance_metric,"distance.") + print("Using FB DeepFace model backend", distance_metric, "distance.") model = FbDeepFace.loadModel() elif model_name == 'DeepID': - print("Using DeepID model backend", distance_metric,"distance.") + print("Using DeepID model backend", distance_metric, "distance.") model = DeepID.loadModel() elif model_name == 'Dlib': - print("Using Dlib ResNet model backend", distance_metric,"distance.") + print("Using Dlib ResNet model backend", distance_metric, "distance.") from deepface.basemodels.DlibResNet import DlibResNet #this is not a must because it is very huge model = DlibResNet() elif model_name == 'Ensemble': print("Ensemble learning enabled") #TODO: include DeepID in ensemble method - + import lightgbm as lgb #lightgbm==2.3.1 - + models = {} - + pbar = tqdm(range(0, len(model_names)), desc='Face recognition models') - + for index in pbar: if index == 0: pbar.set_description("Loading VGG-Face") @@ -579,181 +577,181 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine', elif index == 3: pbar.set_description("Loading DeepFace") models['DeepFace'] = FbDeepFace.loadModel() - + else: - raise ValueError("Invalid model_name passed - ", model_name) + raise ValueError("Invalid model_name passed - ", model_name) else: #model != None print("Already built model is passed") - + if model_name == 'Ensemble': - + import lightgbm as lgb #lightgbm==2.3.1 - + #validate model dictionary because it might be passed from input as pre-trained - + found_models = [] for key, value in model.items(): found_models.append(key) - + if ('VGG-Face' in found_models) and ('Facenet' in found_models) and ('OpenFace' in found_models) and ('DeepFace' in found_models): print("Ensemble learning will be applied for ", found_models," models") else: raise ValueError("You would like to apply ensemble learning and pass pre-built models but models must contain [VGG-Face, Facenet, OpenFace, DeepFace] but you passed "+found_models) - + models = model.copy() - + #threshold = functions.findThreshold(model_name, distance_metric) - + #--------------------------------------- - + file_name = "representations_%s.pkl" % (model_name) file_name = file_name.replace("-", "_").lower() - + if path.exists(db_path+"/"+file_name): - + print("WARNING: Representations for images in ",db_path," folder were previously stored in ", file_name, ". If you added new instances after this file creation, then please delete this file and call find function again. It will create it again.") - + f = open(db_path+'/'+file_name, 'rb') representations = pickle.load(f) - + print("There are ", len(representations)," representations found in ",file_name) - + else: employees = [] - + for r, d, f in os.walk(db_path): # r=root, d=directories, f = files for file in f: if ('.jpg' in file): exact_path = r + "/" + file employees.append(exact_path) - + if len(employees) == 0: raise ValueError("There is no image in ", db_path," folder!") - + #------------------------ #find representations for db images - + representations = [] - + pbar = tqdm(range(0,len(employees)), desc='Finding representations') - + #for employee in employees: for index in pbar: employee = employees[index] - + if model_name != 'Ensemble': - + if model_name == 'Dlib': #non-keras model input_shape = (150, 150, 3) else: #input_shape = model.layers[0].input_shape[1:3] #my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue. - + input_shape = model.layers[0].input_shape - + if type(input_shape) == list: input_shape = input_shape[0][1:3] else: input_shape = input_shape[1:3] - + #--------------------- - + input_shape_x = input_shape[0]; input_shape_y = input_shape[1] - - img = functions.preprocess_face(img = employee, target_size = (input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend) + + img = functions.preprocess_face(img = employee, target_size = (input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend)['processed'] representation = model.predict(img)[0,:] - + instance = [] instance.append(employee) instance.append(representation) - + else: #ensemble learning - + instance = [] instance.append(employee) - + for j in model_names: ensemble_model = models[j] - + #input_shape = model.layers[0].input_shape[1:3] #my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue. - + input_shape = ensemble_model.layers[0].input_shape - + if type(input_shape) == list: input_shape = input_shape[0][1:3] else: input_shape = input_shape[1:3] - + input_shape_x = input_shape[0]; input_shape_y = input_shape[1] - - img = functions.preprocess_face(img = employee, target_size = (input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend) + + img = functions.preprocess_face(img = employee, target_size = (input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend)['processed'] representation = ensemble_model.predict(img)[0,:] instance.append(representation) - + #------------------------------- - + representations.append(instance) - + f = open(db_path+'/'+file_name, "wb") pickle.dump(representations, f) f.close() - + print("Representations stored in ",db_path,"/",file_name," file. Please delete this file when you add new identities in your database.") - + #---------------------------- #we got representations for database - + if model_name != 'Ensemble': df = pd.DataFrame(representations, columns = ["identity", "representation"]) else: #ensemble learning df = pd.DataFrame(representations, columns = ["identity", "VGG-Face_representation", "Facenet_representation", "OpenFace_representation", "DeepFace_representation"]) - + df_base = df.copy() - + resp_obj = [] - + global_pbar = tqdm(range(0,len(img_paths)), desc='Analyzing') for j in global_pbar: img_path = img_paths[j] - + #find representation for passed image - + if model_name == 'Ensemble': for j in model_names: ensemble_model = models[j] - + #input_shape = ensemble_model.layers[0].input_shape[1:3] #my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue. - + input_shape = ensemble_model.layers[0].input_shape - + if type(input_shape) == list: input_shape = input_shape[0][1:3] else: input_shape = input_shape[1:3] - - img = functions.preprocess_face(img = img_path, target_size = input_shape, enforce_detection = enforce_detection, detector_backend = detector_backend) + + img = functions.preprocess_face(img = img_path, target_size = input_shape, enforce_detection = enforce_detection, detector_backend = detector_backend)['processed'] target_representation = ensemble_model.predict(img)[0,:] - + for k in metric_names: distances = [] for index, instance in df.iterrows(): source_representation = instance["%s_representation" % (j)] - + if k == 'cosine': distance = dst.findCosineDistance(source_representation, target_representation) elif k == 'euclidean': distance = dst.findEuclideanDistance(source_representation, target_representation) elif k == 'euclidean_l2': distance = dst.findEuclideanDistance(dst.l2_normalize(source_representation), dst.l2_normalize(target_representation)) - + distances.append(distance) - + if j == 'OpenFace' and k == 'euclidean': continue else: df["%s_%s" % (j, k)] = distances - + #---------------------------------- - + feature_names = [] for j in model_names: for k in metric_names: @@ -762,73 +760,73 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine', else: feature = '%s_%s' % (j, k) feature_names.append(feature) - + #print(df[feature_names].head()) - + x = df[feature_names].values - + #---------------------------------- #lightgbm model home = str(Path.home()) - + if os.path.isfile(home+'/.deepface/weights/face-recognition-ensemble-model.txt') != True: print("face-recognition-ensemble-model.txt will be downloaded...") url = 'https://raw.githubusercontent.com/serengil/deepface/master/deepface/models/face-recognition-ensemble-model.txt' output = home+'/.deepface/weights/face-recognition-ensemble-model.txt' gdown.download(url, output, quiet=False) - + ensemble_model_path = home+'/.deepface/weights/face-recognition-ensemble-model.txt' - + deepface_ensemble = lgb.Booster(model_file = ensemble_model_path) - + y = deepface_ensemble.predict(x) - + verified_labels = []; scores = [] for i in y: verified = np.argmax(i) == 1 score = i[np.argmax(i)] - + verified_labels.append(verified) scores.append(score) - + df['verified'] = verified_labels df['score'] = scores - + df = df[df.verified == True] #df = df[df.score > 0.99] #confidence score df = df.sort_values(by = ["score"], ascending=False).reset_index(drop=True) df = df[['identity', 'verified', 'score']] - + resp_obj.append(df) df = df_base.copy() #restore df for the next iteration - + #---------------------------------- - + if model_name != 'Ensemble': - + if model_name == 'Dlib': #non-keras model input_shape = (150, 150, 3) else: #input_shape = model.layers[0].input_shape[1:3] #my environment returns (None, 224, 224, 3) but some people mentioned that they got [(None, 224, 224, 3)]. I think this is because of version issue. - + input_shape = model.layers[0].input_shape - + if type(input_shape) == list: input_shape = input_shape[0][1:3] else: input_shape = input_shape[1:3] - + #------------------------ - + input_shape_x = input_shape[0]; input_shape_y = input_shape[1] - - img = functions.preprocess_face(img = img_path, target_size = (input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend) + + img = functions.preprocess_face(img = img_path, target_size = (input_shape_y, input_shape_x), enforce_detection = enforce_detection, detector_backend = detector_backend)['processed'] target_representation = model.predict(img)[0,:] - + distances = [] for index, instance in df.iterrows(): source_representation = instance["representation"] - + if distance_metric == 'cosine': distance = dst.findCosineDistance(source_representation, target_representation) elif distance_metric == 'euclidean': @@ -837,33 +835,33 @@ def find(img_path, db_path, model_name ='VGG-Face', distance_metric = 'cosine', distance = dst.findEuclideanDistance(dst.l2_normalize(source_representation), dst.l2_normalize(target_representation)) else: raise ValueError("Invalid distance_metric passed - ", distance_metric) - + distances.append(distance) - + threshold = functions.findThreshold(model_name, distance_metric) - + df["distance"] = distances df = df.drop(columns = ["representation"]) df = df[df.distance <= threshold] - + df = df.sort_values(by = ["distance"], ascending=True).reset_index(drop=True) resp_obj.append(df) df = df_base.copy() #restore df for the next iteration - + toc = time.time() - + print("find function lasts ",toc-tic," seconds") - + if len(resp_obj) == 1: return resp_obj[0] - + return resp_obj - + else: raise ValueError("Passed db_path does not exist!") - + return None - + def stream(db_path = '', model_name ='VGG-Face', distance_metric = 'cosine', enable_face_analysis = True): realtime.analysis(db_path, model_name, distance_metric, enable_face_analysis) diff --git a/deepface/commons/functions.py b/deepface/commons/functions.py index 135546d..1fb24d4 100644 --- a/deepface/commons/functions.py +++ b/deepface/commons/functions.py @@ -18,548 +18,581 @@ import tensorflow as tf import keras import bz2 from deepface.commons import distance -from mtcnn import MTCNN #0.1.0 +from mtcnn import MTCNN # 0.1.0 + def loadBase64Img(uri): - encoded_data = uri.split(',')[1] - nparr = np.fromstring(base64.b64decode(encoded_data), np.uint8) - img = cv2.imdecode(nparr, cv2.IMREAD_COLOR) - return img + encoded_data = uri.split(',')[1] + nparr = np.fromstring(base64.b64decode(encoded_data), np.uint8) + img = cv2.imdecode(nparr, cv2.IMREAD_COLOR) + return img + def initializeFolder(): - - home = str(Path.home()) - - if not os.path.exists(home+"/.deepface"): - os.mkdir(home+"/.deepface") - print("Directory ",home,"/.deepface created") - - if not os.path.exists(home+"/.deepface/weights"): - os.mkdir(home+"/.deepface/weights") - print("Directory ",home,"/.deepface/weights created") - + home = str(Path.home()) + + if not os.path.exists(home + "/.deepface"): + os.mkdir(home + "/.deepface") + print("Directory ", home, "/.deepface created") + + if not os.path.exists(home + "/.deepface/weights"): + os.mkdir(home + "/.deepface/weights") + print("Directory ", home, "/.deepface/weights created") + + def findThreshold(model_name, distance_metric): - - threshold = 0.40 - - if model_name == 'VGG-Face': - if distance_metric == 'cosine': - threshold = 0.40 - elif distance_metric == 'euclidean': - threshold = 0.55 - elif distance_metric == 'euclidean_l2': - threshold = 0.75 - - elif model_name == 'OpenFace': - if distance_metric == 'cosine': - threshold = 0.10 - elif distance_metric == 'euclidean': - threshold = 0.55 - elif distance_metric == 'euclidean_l2': - threshold = 0.55 - - elif model_name == 'Facenet': - if distance_metric == 'cosine': - threshold = 0.40 - elif distance_metric == 'euclidean': - threshold = 10 - elif distance_metric == 'euclidean_l2': - threshold = 0.80 - - elif model_name == 'DeepFace': - if distance_metric == 'cosine': - threshold = 0.23 - elif distance_metric == 'euclidean': - threshold = 64 - elif distance_metric == 'euclidean_l2': - threshold = 0.64 - - elif model_name == 'DeepID': - if distance_metric == 'cosine': - threshold = 0.015 - elif distance_metric == 'euclidean': - threshold = 45 - elif distance_metric == 'euclidean_l2': - threshold = 0.17 - - elif model_name == 'Dlib': - if distance_metric == 'cosine': - threshold = 0.07 - elif distance_metric == 'euclidean': - threshold = 0.60 - elif distance_metric == 'euclidean_l2': - threshold = 0.60 - - return threshold + threshold = 0.40 + + if model_name == 'VGG-Face': + if distance_metric == 'cosine': + threshold = 0.40 + elif distance_metric == 'euclidean': + threshold = 0.55 + elif distance_metric == 'euclidean_l2': + threshold = 0.75 + + elif model_name == 'OpenFace': + if distance_metric == 'cosine': + threshold = 0.10 + elif distance_metric == 'euclidean': + threshold = 0.55 + elif distance_metric == 'euclidean_l2': + threshold = 0.55 + + elif model_name == 'Facenet': + if distance_metric == 'cosine': + threshold = 0.40 + elif distance_metric == 'euclidean': + threshold = 10 + elif distance_metric == 'euclidean_l2': + threshold = 0.80 + + elif model_name == 'DeepFace': + if distance_metric == 'cosine': + threshold = 0.23 + elif distance_metric == 'euclidean': + threshold = 64 + elif distance_metric == 'euclidean_l2': + threshold = 0.64 + + elif model_name == 'DeepID': + if distance_metric == 'cosine': + threshold = 0.015 + elif distance_metric == 'euclidean': + threshold = 45 + elif distance_metric == 'euclidean_l2': + threshold = 0.17 + + elif model_name == 'Dlib': + if distance_metric == 'cosine': + threshold = 0.07 + elif distance_metric == 'euclidean': + threshold = 0.60 + elif distance_metric == 'euclidean_l2': + threshold = 0.60 + + return threshold + def get_opencv_path(): - opencv_home = cv2.__file__ - folders = opencv_home.split(os.path.sep)[0:-1] - - path = folders[0] - for folder in folders[1:]: - path = path + "/" + folder - - return path+"/data/" + opencv_home = cv2.__file__ + folders = opencv_home.split(os.path.sep)[0:-1] + + path = folders[0] + for folder in folders[1:]: + path = path + "/" + folder + + return path + "/data/" + def load_image(img): - - exact_image = False - if type(img).__module__ == np.__name__: - exact_image = True - - base64_img = False - if len(img) > 11 and img[0:11] == "data:image/": - base64_img = True - - #--------------------------- - - if base64_img == True: - img = loadBase64Img(img) - - elif exact_image != True: #image path passed as input - if os.path.isfile(img) != True: - raise ValueError("Confirm that ",img," exists") - - img = cv2.imread(img) - - return img - -def detect_face(img, detector_backend = 'opencv', grayscale = False, enforce_detection = True): - - home = str(Path.home()) - - if detector_backend == 'opencv': - - #get opencv configuration up first - opencv_path = get_opencv_path() - face_detector_path = opencv_path+"haarcascade_frontalface_default.xml" - - if os.path.isfile(face_detector_path) != True: - raise ValueError("Confirm that opencv is installed on your environment! Expected path ",face_detector_path," violated.") - - face_detector = cv2.CascadeClassifier(face_detector_path) - - #-------------------------- - - faces = [] - - try: - faces = face_detector.detectMultiScale(img, 1.3, 5) - except: - pass - - if len(faces) > 0: - x,y,w,h = faces[0] #focus on the 1st face found in the image - detected_face = img[int(y):int(y+h), int(x):int(x+w)] - return detected_face - - else: #if no face detected - - if enforce_detection != True: - return img - - else: - raise ValueError("Face could not be detected. Please confirm that the picture is a face photo or consider to set enforce_detection param to False.") + exact_image = False + if type(img).__module__ == np.__name__: + exact_image = True + + base64_img = False + if len(img) > 11 and img[0:11] == "data:image/": + base64_img = True + + # --------------------------- + + if base64_img == True: + img = loadBase64Img(img) + + elif exact_image != True: # image path passed as input + if os.path.isfile(img) != True: + raise ValueError("Confirm that ", img, " exists") + + img = cv2.imread(img) + + return img + + +def detect_face(img, detector_backend='opencv', grayscale=False, enforce_detection=True): + home = str(Path.home()) + + if detector_backend == 'opencv': + + # get opencv configuration up first + opencv_path = get_opencv_path() + face_detector_path = opencv_path + "haarcascade_frontalface_default.xml" + + if os.path.isfile(face_detector_path) != True: + raise ValueError("Confirm that opencv is installed on your environment! Expected path ", face_detector_path, + " violated.") + + face_detector = cv2.CascadeClassifier(face_detector_path) + + # -------------------------- + + faces = [] + + try: + faces = face_detector.detectMultiScale(img, 1.3, 5) + except: + pass + + if len(faces) > 0: + detected_faces = [] + for face in faces: + print(face) + x, y, w, h = face + detected_face = img[int(y):int(y + h), int(x):int(x + w)] + detected_faces.append(detected_face) + return detected_faces + + else: # if no face detected + + if enforce_detection != True: + return img + + else: + raise ValueError( + "Face could not be detected. Please confirm that the picture is a face photo or consider to set enforce_detection param to False.") + + elif detector_backend == 'ssd': + + # --------------------------- + # check required ssd model exists in the home/.deepface/weights folder + + # model structure + if os.path.isfile(home + '/.deepface/weights/deploy.prototxt') != True: + print("deploy.prototxt will be downloaded...") + + url = "https://github.com/opencv/opencv/raw/3.4.0/samples/dnn/face_detector/deploy.prototxt" + + output = home + '/.deepface/weights/deploy.prototxt' + + gdown.download(url, output, quiet=False) + + # pre-trained weights + if os.path.isfile(home + '/.deepface/weights/res10_300x300_ssd_iter_140000.caffemodel') != True: + print("res10_300x300_ssd_iter_140000.caffemodel will be downloaded...") + + url = "https://github.com/opencv/opencv_3rdparty/raw/dnn_samples_face_detector_20170830/res10_300x300_ssd_iter_140000.caffemodel" + + output = home + '/.deepface/weights/res10_300x300_ssd_iter_140000.caffemodel' + + gdown.download(url, output, quiet=False) + + # --------------------------- + + ssd_detector = cv2.dnn.readNetFromCaffe( + home + "/.deepface/weights/deploy.prototxt", + home + "/.deepface/weights/res10_300x300_ssd_iter_140000.caffemodel" + ) + + ssd_labels = ["img_id", "is_face", "confidence", "left", "top", "right", "bottom"] + + target_size = (300, 300) + + base_img = img.copy() # we will restore base_img to img later + + original_size = img.shape + + img = cv2.resize(img, target_size) + + aspect_ratio_x = (original_size[1] / target_size[1]) + aspect_ratio_y = (original_size[0] / target_size[0]) + + imageBlob = cv2.dnn.blobFromImage(image=img) + + ssd_detector.setInput(imageBlob) + detections = ssd_detector.forward() + + detections_df = pd.DataFrame(detections[0][0], columns=ssd_labels) + + detections_df = detections_df[detections_df['is_face'] == 1] # 0: background, 1: face + detections_df = detections_df[detections_df['confidence'] >= 0.90] + + detections_df['left'] = (detections_df['left'] * 300).astype(int) + detections_df['bottom'] = (detections_df['bottom'] * 300).astype(int) + detections_df['right'] = (detections_df['right'] * 300).astype(int) + detections_df['top'] = (detections_df['top'] * 300).astype(int) + + if detections_df.shape[0] > 0: + + # TODO: sort detections_df + + # get the first face in the image + instance = detections_df.iloc[0] + + left = instance["left"] + right = instance["right"] + bottom = instance["bottom"] + top = instance["top"] + + detected_face = base_img[int(top * aspect_ratio_y):int(bottom * aspect_ratio_y), + int(left * aspect_ratio_x):int(right * aspect_ratio_x)] + + return detected_face + + else: # if no face detected + + if enforce_detection != True: + img = base_img.copy() + return img + + else: + raise ValueError( + "Face could not be detected. Please confirm that the picture is a face photo or consider to set enforce_detection param to False.") + + elif detector_backend == 'dlib': + import \ + dlib # this is not a must library within deepface. that's why, I didn't put this import to a global level. version: 19.20.0 + + detector = dlib.get_frontal_face_detector() + + detections = detector(img, 1) + + if len(detections) > 0: + + for idx, d in enumerate(detections): + left = d.left(); + right = d.right() + top = d.top(); + bottom = d.bottom() + + detected_face = img[top:bottom, left:right] + + return detected_face + + else: # if no face detected + + if enforce_detection != True: + return img + + else: + raise ValueError( + "Face could not be detected. Please confirm that the picture is a face photo or consider to set enforce_detection param to False.") + + elif detector_backend == 'mtcnn': + + mtcnn_detector = MTCNN() + + detections = mtcnn_detector.detect_faces(img) + + if len(detections) > 0: + detected_faces = [] + for detection in detections: + x, y, w, h = detection["box"] + detected_face = img[int(y):int(y + h), int(x):int(x + w)] + detected_faces.append(detected_face) + return detected_faces + + else: # if no face detected + if enforce_detection != True: + return img + + else: + raise ValueError( + "Face could not be detected. Please confirm that the picture is a face photo or consider to set enforce_detection param to False.") + + else: + detectors = ['opencv', 'ssd', 'dlib', 'mtcnn'] + raise ValueError("Valid backends are ", detectors, " but you passed ", detector_backend) + + return 0 - elif detector_backend == 'ssd': - - #--------------------------- - #check required ssd model exists in the home/.deepface/weights folder - - #model structure - if os.path.isfile(home+'/.deepface/weights/deploy.prototxt') != True: - - print("deploy.prototxt will be downloaded...") - - url = "https://github.com/opencv/opencv/raw/3.4.0/samples/dnn/face_detector/deploy.prototxt" - - output = home+'/.deepface/weights/deploy.prototxt' - - gdown.download(url, output, quiet=False) - - - #pre-trained weights - if os.path.isfile(home+'/.deepface/weights/res10_300x300_ssd_iter_140000.caffemodel') != True: - - print("res10_300x300_ssd_iter_140000.caffemodel will be downloaded...") - - url = "https://github.com/opencv/opencv_3rdparty/raw/dnn_samples_face_detector_20170830/res10_300x300_ssd_iter_140000.caffemodel" - - output = home+'/.deepface/weights/res10_300x300_ssd_iter_140000.caffemodel' - - gdown.download(url, output, quiet=False) - - #--------------------------- - - ssd_detector = cv2.dnn.readNetFromCaffe( - home+"/.deepface/weights/deploy.prototxt", - home+"/.deepface/weights/res10_300x300_ssd_iter_140000.caffemodel" - ) - - ssd_labels = ["img_id", "is_face", "confidence", "left", "top", "right", "bottom"] - - target_size = (300, 300) - - base_img = img.copy() #we will restore base_img to img later - - original_size = img.shape - - img = cv2.resize(img, target_size) - - aspect_ratio_x = (original_size[1] / target_size[1]) - aspect_ratio_y = (original_size[0] / target_size[0]) - - imageBlob = cv2.dnn.blobFromImage(image = img) - - ssd_detector.setInput(imageBlob) - detections = ssd_detector.forward() - - detections_df = pd.DataFrame(detections[0][0], columns = ssd_labels) - - detections_df = detections_df[detections_df['is_face'] == 1] #0: background, 1: face - detections_df = detections_df[detections_df['confidence'] >= 0.90] - - detections_df['left'] = (detections_df['left'] * 300).astype(int) - detections_df['bottom'] = (detections_df['bottom'] * 300).astype(int) - detections_df['right'] = (detections_df['right'] * 300).astype(int) - detections_df['top'] = (detections_df['top'] * 300).astype(int) - - if detections_df.shape[0] > 0: - - #TODO: sort detections_df - - #get the first face in the image - instance = detections_df.iloc[0] - - left = instance["left"] - right = instance["right"] - bottom = instance["bottom"] - top = instance["top"] - - detected_face = base_img[int(top*aspect_ratio_y):int(bottom*aspect_ratio_y), int(left*aspect_ratio_x):int(right*aspect_ratio_x)] - - return detected_face - - else: #if no face detected - - if enforce_detection != True: - img = base_img.copy() - return img - - else: - raise ValueError("Face could not be detected. Please confirm that the picture is a face photo or consider to set enforce_detection param to False.") - - elif detector_backend == 'dlib': - import dlib #this is not a must library within deepface. that's why, I didn't put this import to a global level. version: 19.20.0 - - detector = dlib.get_frontal_face_detector() - - detections = detector(img, 1) - - if len(detections) > 0: - - for idx, d in enumerate(detections): - left = d.left(); right = d.right() - top = d.top(); bottom = d.bottom() - - detected_face = img[top:bottom, left:right] - - return detected_face - - else: #if no face detected - - if enforce_detection != True: - return img - - else: - raise ValueError("Face could not be detected. Please confirm that the picture is a face photo or consider to set enforce_detection param to False.") - - elif detector_backend == 'mtcnn': - - mtcnn_detector = MTCNN() - - detections = mtcnn_detector.detect_faces(img) - - if len(detections) > 0: - detection = detections[0] - x, y, w, h = detection["box"] - detected_face = img[int(y):int(y+h), int(x):int(x+w)] - return detected_face - - else: #if no face detected - if enforce_detection != True: - return img - - else: - raise ValueError("Face could not be detected. Please confirm that the picture is a face photo or consider to set enforce_detection param to False.") - - else: - detectors = ['opencv', 'ssd', 'dlib', 'mtcnn'] - raise ValueError("Valid backends are ", detectors," but you passed ", detector_backend) - - return 0 def alignment_procedure(img, left_eye, right_eye): - - #this function aligns given face in img based on left and right eye coordinates - - left_eye_x, left_eye_y = left_eye - right_eye_x, right_eye_y = right_eye - - #----------------------- - #find rotation direction - - if left_eye_y > right_eye_y: - point_3rd = (right_eye_x, left_eye_y) - direction = -1 #rotate same direction to clock - else: - point_3rd = (left_eye_x, right_eye_y) - direction = 1 #rotate inverse direction of clock - - #----------------------- - #find length of triangle edges - - a = distance.findEuclideanDistance(np.array(left_eye), np.array(point_3rd)) - b = distance.findEuclideanDistance(np.array(right_eye), np.array(point_3rd)) - c = distance.findEuclideanDistance(np.array(right_eye), np.array(left_eye)) - - #----------------------- - - #apply cosine rule - - if b != 0 and c != 0: #this multiplication causes division by zero in cos_a calculation - - cos_a = (b*b + c*c - a*a)/(2*b*c) - angle = np.arccos(cos_a) #angle in radian - angle = (angle * 180) / math.pi #radian to degree - - #----------------------- - #rotate base image - - if direction == -1: - angle = 90 - angle - - img = Image.fromarray(img) - img = np.array(img.rotate(direction * angle)) - - #----------------------- - - return img #return img anyway - -def align_face(img, detector_backend = 'opencv'): - - home = str(Path.home()) - - if (detector_backend == 'opencv') or (detector_backend == 'ssd'): - - opencv_path = get_opencv_path() - eye_detector_path = opencv_path+"haarcascade_eye.xml" - eye_detector = cv2.CascadeClassifier(eye_detector_path) - - detected_face_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #eye detector expects gray scale image - - eyes = eye_detector.detectMultiScale(detected_face_gray) - - if len(eyes) >= 2: - - #find the largest 2 eye - - base_eyes = eyes[:, 2] - - items = [] - for i in range(0, len(base_eyes)): - item = (base_eyes[i], i) - items.append(item) - - df = pd.DataFrame(items, columns = ["length", "idx"]).sort_values(by=['length'], ascending=False) - - eyes = eyes[df.idx.values[0:2]] #eyes variable stores the largest 2 eye - - #----------------------- - #decide left and right eye - - eye_1 = eyes[0]; eye_2 = eyes[1] - - if eye_1[0] < eye_2[0]: - left_eye = eye_1; right_eye = eye_2 - else: - left_eye = eye_2; right_eye = eye_1 - - #----------------------- - #find center of eyes - - left_eye = (int(left_eye[0] + (left_eye[2] / 2)), int(left_eye[1] + (left_eye[3] / 2))) - right_eye = (int(right_eye[0] + (right_eye[2]/2)), int(right_eye[1] + (right_eye[3]/2))) - - img = alignment_procedure(img, left_eye, right_eye) - - return img #return img anyway - - elif detector_backend == 'dlib': - - #check required file exists in the home/.deepface/weights folder - - if os.path.isfile(home+'/.deepface/weights/shape_predictor_5_face_landmarks.dat') != True: - - print("shape_predictor_5_face_landmarks.dat.bz2 is going to be downloaded") - - url = "http://dlib.net/files/shape_predictor_5_face_landmarks.dat.bz2" - output = home+'/.deepface/weights/'+url.split("/")[-1] - - gdown.download(url, output, quiet=False) - - zipfile = bz2.BZ2File(output) - data = zipfile.read() - newfilepath = output[:-4] #discard .bz2 extension - open(newfilepath, 'wb').write(data) - - #------------------------------ - - import dlib #this is not a must dependency in deepface - - detector = dlib.get_frontal_face_detector() - sp = dlib.shape_predictor(home+"/.deepface/weights/shape_predictor_5_face_landmarks.dat") - - detections = detector(img, 1) - - if len(detections) > 0: - detected_face = detections[0] - img_shape = sp(img, detected_face) - img = dlib.get_face_chip(img, img_shape, size = img.shape[0]) - - return img #return img anyway - - elif detector_backend == 'mtcnn': - - mtcnn_detector = MTCNN() - detections = mtcnn_detector.detect_faces(img) - - if len(detections) > 0: - detection = detections[0] - - keypoints = detection["keypoints"] - left_eye = keypoints["left_eye"] - right_eye = keypoints["right_eye"] - - img = alignment_procedure(img, left_eye, right_eye) - - return img #return img anyway - -def preprocess_face(img, target_size=(224, 224), grayscale = False, enforce_detection = True, detector_backend = 'opencv'): - - #img might be path, base64 or numpy array. Convert it to numpy whatever it is. - img = load_image(img) - base_img = img.copy() - - img = detect_face(img = img, detector_backend = detector_backend, grayscale = grayscale, enforce_detection = enforce_detection) - - #-------------------------- - - if img.shape[0] > 0 and img.shape[1] > 0: - img = align_face(img = img, detector_backend = detector_backend) - else: - - if enforce_detection == True: - raise ValueError("Detected face shape is ", img.shape,". Consider to set enforce_detection argument to False.") - else: #restore base image - img = base_img.copy() - - #-------------------------- - - #post-processing - if grayscale == True: - img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) - - img = cv2.resize(img, target_size) - img_pixels = image.img_to_array(img) - img_pixels = np.expand_dims(img_pixels, axis = 0) - img_pixels /= 255 #normalize input in [0, 1] - - return img_pixels - + # this function aligns given face in img based on left and right eye coordinates + + left_eye_x, left_eye_y = left_eye + right_eye_x, right_eye_y = right_eye + + # ----------------------- + # find rotation direction + + if left_eye_y > right_eye_y: + point_3rd = (right_eye_x, left_eye_y) + direction = -1 # rotate same direction to clock + else: + point_3rd = (left_eye_x, right_eye_y) + direction = 1 # rotate inverse direction of clock + + # ----------------------- + # find length of triangle edges + + a = distance.findEuclideanDistance(np.array(left_eye), np.array(point_3rd)) + b = distance.findEuclideanDistance(np.array(right_eye), np.array(point_3rd)) + c = distance.findEuclideanDistance(np.array(right_eye), np.array(left_eye)) + + # ----------------------- + + # apply cosine rule + + if b != 0 and c != 0: # this multiplication causes division by zero in cos_a calculation + + cos_a = (b * b + c * c - a * a) / (2 * b * c) + angle = np.arccos(cos_a) # angle in radian + angle = (angle * 180) / math.pi # radian to degree + + # ----------------------- + # rotate base image + + if direction == -1: + angle = 90 - angle + + img = Image.fromarray(img) + img = np.array(img.rotate(direction * angle)) + + # ----------------------- + + return img # return img anyway + + +def align_face(img, detector_backend='opencv'): + home = str(Path.home()) + + if (detector_backend == 'opencv') or (detector_backend == 'ssd'): + + opencv_path = get_opencv_path() + eye_detector_path = opencv_path + "haarcascade_eye.xml" + eye_detector = cv2.CascadeClassifier(eye_detector_path) + + detected_face_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # eye detector expects gray scale image + + eyes = eye_detector.detectMultiScale(detected_face_gray) + + if len(eyes) >= 2: + + # find the largest 2 eye + + base_eyes = eyes[:, 2] + + items = [] + for i in range(0, len(base_eyes)): + item = (base_eyes[i], i) + items.append(item) + + df = pd.DataFrame(items, columns=["length", "idx"]).sort_values(by=['length'], ascending=False) + + eyes = eyes[df.idx.values[0:2]] # eyes variable stores the largest 2 eye + + # ----------------------- + # decide left and right eye + + eye_1 = eyes[0]; + eye_2 = eyes[1] + + if eye_1[0] < eye_2[0]: + left_eye = eye_1; + right_eye = eye_2 + else: + left_eye = eye_2; + right_eye = eye_1 + + # ----------------------- + # find center of eyes + + left_eye = (int(left_eye[0] + (left_eye[2] / 2)), int(left_eye[1] + (left_eye[3] / 2))) + right_eye = (int(right_eye[0] + (right_eye[2] / 2)), int(right_eye[1] + (right_eye[3] / 2))) + + img = alignment_procedure(img, left_eye, right_eye) + + return img # return img anyway + + elif detector_backend == 'dlib': + + # check required file exists in the home/.deepface/weights folder + + if os.path.isfile(home + '/.deepface/weights/shape_predictor_5_face_landmarks.dat') != True: + print("shape_predictor_5_face_landmarks.dat.bz2 is going to be downloaded") + + url = "http://dlib.net/files/shape_predictor_5_face_landmarks.dat.bz2" + output = home + '/.deepface/weights/' + url.split("/")[-1] + + gdown.download(url, output, quiet=False) + + zipfile = bz2.BZ2File(output) + data = zipfile.read() + newfilepath = output[:-4] # discard .bz2 extension + open(newfilepath, 'wb').write(data) + + # ------------------------------ + + import dlib # this is not a must dependency in deepface + + detector = dlib.get_frontal_face_detector() + sp = dlib.shape_predictor(home + "/.deepface/weights/shape_predictor_5_face_landmarks.dat") + + detections = detector(img, 1) + + if len(detections) > 0: + detected_face = detections[0] + img_shape = sp(img, detected_face) + img = dlib.get_face_chip(img, img_shape, size=img.shape[0]) + + return img # return img anyway + + elif detector_backend == 'mtcnn': + + mtcnn_detector = MTCNN() + detections = mtcnn_detector.detect_faces(img) + + if len(detections) > 0: + detection = detections[0] + + keypoints = detection["keypoints"] + left_eye = keypoints["left_eye"] + right_eye = keypoints["right_eye"] + + img = alignment_procedure(img, left_eye, right_eye) + + return img # return img anyway + + +def preprocess_face(img, target_size=(224, 224), grayscale=False, enforce_detection=True, detector_backend='opencv'): + # img might be path, base64 or numpy array. Convert it to numpy whatever it is. + img = load_image(img) + base_img = img.copy() + + imgs = detect_face(img=img, detector_backend=detector_backend, grayscale=grayscale, + enforce_detection=enforce_detection) + + # -------------------------- + + for i in range(len(imgs)): + + img = imgs[i] + + if img.shape[0] > 0 and img.shape[1] > 0: + imgs[i] = align_face(img=img, detector_backend=detector_backend) + else: + + if enforce_detection == True: + raise ValueError("Detected face shape is ", img.shape, + ". Consider to set enforce_detection argument to False.") + else: # restore base image + imgs[i] = base_img.copy() + + # -------------------------- + + # post-processing + + pixels = [] + + for img in imgs: + + if grayscale == True: + img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) + + img = cv2.resize(img, target_size) + img_pixels = image.img_to_array(img) + img_pixels = np.expand_dims(img_pixels, axis=0) + img_pixels /= 255 # normalize input in [0, 1] + + pixels.append(img_pixels) + + return {'processed': pixels, 'original': imgs} + + def allocateMemory(): - - #find allocated memories - gpu_indexes = [] - memory_usage_percentages = []; available_memories = []; total_memories = []; utilizations = [] - power_usages = []; power_capacities = [] - - try: - result = subprocess.check_output(['nvidia-smi']) + # find allocated memories + gpu_indexes = [] + memory_usage_percentages = []; + available_memories = []; + total_memories = []; + utilizations = [] + power_usages = []; + power_capacities = [] - dashboard = result.decode("utf-8").split("=|") + try: + result = subprocess.check_output(['nvidia-smi']) - dashboard = dashboard[1].split("\n") - - gpu_idx = 0 - for line in dashboard: - if ("MiB" in line): - power_info = line.split("|")[1] - power_capacity = int(power_info.split("/")[-1].replace("W", "")) - power_usage = int((power_info.split("/")[-2]).strip().split(" ")[-1].replace("W", "")) - - power_usages.append(power_usage) - power_capacities.append(power_capacity) - - #---------------------------- - - memory_info = line.split("|")[2].replace("MiB","").split("/") - utilization_info = int(line.split("|")[3].split("%")[0]) - - allocated = int(memory_info[0]) - total_memory = int(memory_info[1]) - available_memory = total_memory - allocated - - total_memories.append(total_memory) - available_memories.append(available_memory) - memory_usage_percentages.append(round(100*int(allocated)/int(total_memory), 4)) - utilizations.append(utilization_info) - gpu_indexes.append(gpu_idx) - - gpu_idx = gpu_idx + 1 - - gpu_count = gpu_idx * 1 - - except Exception as err: - gpu_count = 0 - #print(str(err)) - - #------------------------------ - - df = pd.DataFrame(gpu_indexes, columns = ["gpu_index"]) - df["total_memories_in_mb"] = total_memories - df["available_memories_in_mb"] = available_memories - df["memory_usage_percentage"] = memory_usage_percentages - df["utilizations"] = utilizations - df["power_usages_in_watts"] = power_usages - df["power_capacities_in_watts"] = power_capacities - - df = df.sort_values(by = ["available_memories_in_mb"], ascending = False).reset_index(drop = True) - - #------------------------------ - - required_memory = 10000 #All deepface models require 9016 MiB - - if df.shape[0] > 0: #has gpu - if df.iloc[0].available_memories_in_mb > required_memory: - my_gpu = str(int(df.iloc[0].gpu_index)) - os.environ["CUDA_VISIBLE_DEVICES"] = my_gpu - - #------------------------------ - #tf allocates all memory by default - #this block avoids greedy approach - - config = tf.ConfigProto() - config.gpu_options.allow_growth = True - session = tf.Session(config=config) - keras.backend.set_session(session) - - print("DeepFace will run on GPU (gpu_", my_gpu,")") - else: - #this case has gpu but no enough memory to allocate - os.environ["CUDA_VISIBLE_DEVICES"] = "" #run it on cpu - print("Even though the system has GPUs, there is no enough space in memory to allocate.") - print("DeepFace will run on CPU") - else: - print("DeepFace will run on CPU") + dashboard = result.decode("utf-8").split("=|") + + dashboard = dashboard[1].split("\n") + + gpu_idx = 0 + for line in dashboard: + if ("MiB" in line): + power_info = line.split("|")[1] + power_capacity = int(power_info.split("/")[-1].replace("W", "")) + power_usage = int((power_info.split("/")[-2]).strip().split(" ")[-1].replace("W", "")) + + power_usages.append(power_usage) + power_capacities.append(power_capacity) + + # ---------------------------- + + memory_info = line.split("|")[2].replace("MiB", "").split("/") + utilization_info = int(line.split("|")[3].split("%")[0]) + + allocated = int(memory_info[0]) + total_memory = int(memory_info[1]) + available_memory = total_memory - allocated + + total_memories.append(total_memory) + available_memories.append(available_memory) + memory_usage_percentages.append(round(100 * int(allocated) / int(total_memory), 4)) + utilizations.append(utilization_info) + gpu_indexes.append(gpu_idx) + + gpu_idx = gpu_idx + 1 + + gpu_count = gpu_idx * 1 + + except Exception as err: + gpu_count = 0 + # print(str(err)) + + # ------------------------------ + + df = pd.DataFrame(gpu_indexes, columns=["gpu_index"]) + df["total_memories_in_mb"] = total_memories + df["available_memories_in_mb"] = available_memories + df["memory_usage_percentage"] = memory_usage_percentages + df["utilizations"] = utilizations + df["power_usages_in_watts"] = power_usages + df["power_capacities_in_watts"] = power_capacities + + df = df.sort_values(by=["available_memories_in_mb"], ascending=False).reset_index(drop=True) + + # ------------------------------ + + required_memory = 10000 # All deepface models require 9016 MiB + + if df.shape[0] > 0: # has gpu + if df.iloc[0].available_memories_in_mb > required_memory: + my_gpu = str(int(df.iloc[0].gpu_index)) + os.environ["CUDA_VISIBLE_DEVICES"] = my_gpu + + # ------------------------------ + # tf allocates all memory by default + # this block avoids greedy approach + + config = tf.ConfigProto() + config.gpu_options.allow_growth = True + session = tf.Session(config=config) + keras.backend.set_session(session) + + print("DeepFace will run on GPU (gpu_", my_gpu, ")") + else: + # this case has gpu but no enough memory to allocate + os.environ["CUDA_VISIBLE_DEVICES"] = "" # run it on cpu + print("Even though the system has GPUs, there is no enough space in memory to allocate.") + print("DeepFace will run on CPU") + else: + print("DeepFace will run on CPU") diff --git a/my_deepface.ipynb b/my_deepface.ipynb new file mode 100644 index 0000000..8c756b9 --- /dev/null +++ b/my_deepface.ipynb @@ -0,0 +1,441 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": true, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [], + "source": [ + "from deepface import DeepFace\n", + "import os\n", + "import cv2\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "outputs": [], + "source": [ + "# read images\n", + "imgs = []\n", + "img_dir = 'test_imgs/'\n", + "for img in os.listdir(img_dir):\n", + " if img.endswith('jpg') or img.endswith('jpeg'):\n", + " img_path = os.path.join(img_dir, img)\n", + " imgs.append(img_path)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 3, + "outputs": [ + { + "data": { + "text/plain": "" + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
", + "image/png": "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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "img1 = plt.imread(imgs[0])\n", + "plt.imshow(img1)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 4, + "outputs": [ + { + "data": { + "text/plain": "" + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
", + "image/png": "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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "img2 = plt.imread(imgs[1])\n", + "plt.imshow(img2)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 5, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Action: emotion: 100%|██████████| 3/3 [00:01<00:00, 2.11it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[262 48 88 88]\n", + "[57 68 88 88]\n", + "[649 54 99 99]\n", + "[448 57 92 92]\n", + "[450 251 87 87]\n", + "[831 250 96 96]\n", + "[264 255 85 85]\n", + "[653 272 84 84]\n", + "[448 438 96 96]\n", + "[649 446 101 101]\n", + "[256 456 93 93]\n", + "[643 644 104 104]\n", + "[ 65 639 79 79]\n", + "[847 641 86 86]\n", + "[248 655 114 114]\n", + "[643 838 91 91]\n", + "[835 819 92 92]\n", + "[450 830 93 93]\n", + "[256 832 88 88]\n", + "[262 48 88 88]\n", + "[649 54 99 99]\n", + "[57 68 88 88]\n", + "[448 57 92 92]\n", + "[450 251 87 87]\n", + "[653 272 84 84]\n", + "[831 250 96 96]\n", + "[264 255 85 85]\n", + "[448 438 96 96]\n", + "[256 456 93 93]\n", + "[649 446 101 101]\n", + "[643 644 104 104]\n", + "[ 65 639 79 79]\n", + "[847 641 86 86]\n", + "[248 655 114 114]\n", + "[835 819 92 92]\n", + "[450 830 93 93]\n", + "[256 832 88 88]\n", + "[643 838 91 91]\n" + ] + } + ], + "source": [ + "demography, imgs = DeepFace.analyze(imgs[0], actions = ['age', 'gender', 'emotion'])\n", + "# print(\"Age: \", demography[\"age\"])\n", + "# print(\"Gender: \", demography[\"gender\"])\n", + "# print(\"Emotion: \", demography[\"dominant_emotion\"])" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 24, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Age: 34.399849031832304\n", + "Gender: Woman\n", + "Emotion: happy\n" + ] + }, + { + "data": { + "text/plain": "" + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
", + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAPsAAAD7CAYAAACscuKmAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8vihELAAAACXBIWXMAAAsTAAALEwEAmpwYAAEAAElEQVR4nOz9W6wt67bfB/3ad6mq3sdlzrlu+3L2Pj7Hl2AZEjkiCTIRCsQkgGTJEooCthQFJUpewgMCJCxewkMewgsICQSyRISRECbiIgIKQhFKiPJAFAIIC5sY5/ic47Mva6+15pxjjH6pqu/SeGjfV72PufZl7kuWfXJWLfU1xuyj9+rVq6p9rbV/+7d/E1Xl6+3r7evtP/yb+9t9AF9vX29fb1/N9rWxf719vf0B2b429q+3r7c/INvXxv719vX2B2T72ti/3r7e/oBsXxv719vX2x+Q7ZcydhH5z4vIvycif0NE/sKv6qC+3r7evt5+9Zv8onV2EfHAXwf+EeD3gH8H+HOq+ld/dYf39fb19vX2q9rCL/HefwD4G6r6WwAi8peBPwv8RGMXka8ZPF/R9vEHL/i1b36Cd0ItGbQCCiiqSikVrUpOlZQKqCDiEAQQAHtdzagqIQohOETs7yKCiEfEUaqS1kypyrpmUi7bcYhAHAI+OECptSCA9w4ngnNC8M5e2DZVRWtFUara8YoI4hyqUKt9nVIruVRQ+2aoULVSa8U5YRgDzjlqqZRSERGC94iI7V/tjd3haVXbvyol22eD8KWbVvp5AG1/rdoPgu272P4V5wTn7D3e2bmjfa/2jUHAieCdA6FdB3g6H3l7eNo+5302VZUf9/wvY+y/Bvytq3//HvCf+CX29wdyC8Hjvbd/XF9Peeff77XZG0SE/9Kf+dP8C//Nf4a73cj8+AVlmYGEyErOhcPbI+uy8tkPD/zw9x5BPdHf4YgIHtSR8sLj4QtKWfnwGxMffDzinCf4CecCw/iCYbjjcFj4ve+95nha+d2/9Rk/+PQNCKgDFxzf/u4HvProjlIW1vUJkcrL2x03U2S/G3l5f4v3llGqQs4ry3qm1MIxLaScCXEgjnu0CsdDJa3K49OZ12+P1Aq5eFQd5+XEaT4yTQPf/UMfc3MzcXg68fh4IobAB/cvGGMkzStpXqAqNdnCty6Fda3MS+b125k1V0p1FHWoQG1G7OOI8xGA2hbPZc2kXHHO4YJdz7yulJLZjQN3d3ui9+x3I2OM1JLQvLSFrCCi7KaB25sJ5xzeeQT4v/6V/zv/h3/732BJK6XWX+ge69svY+zvtYnIPwv8s/9Bf87vx20cB/7RP/0P8ff/fX/SVvrajbWt7Ju30OZ1qvldVfM3G+Ki7bUKNYMqf++f+GMMPkBVYhjxIqDePIRzxDGgokz7idsXhZqhLJVaEiUnSoJaMw4B5zk8Hpnnt4QwsN+9wIfI3YsB5yJIYX874IJjfzOx2+0otbLkjFY4Hs4ghRCFaTfgHeSkHMsK1THFjHPCsmRyKYQghDjgnOK04LRSi7LOCyB4F3CjY18GSoVclHmFXGBJjpwqp7rw/e9/RoyO9awsp0oIgXR0xBiIzhG9e3aOxQtxqBSFGD2IUCWg2HnLtb1UAC3tbYoAu3FgNzlqVUotqCoueKoTYgg4LCo5n2ZmzngHQSxisYgJaoFlyebhvSII33j5Cf+p/+jfz8Pxif/v7/0Wb4+Pv/D99ssY+/eA7179+zvtuWebqv5F4C/C12H8u9s4jvyjf/of4p/5p/68ha4t/LUQWZCqUM2IaylUrThVvLYw2bWHVrtTtEJaoBZEbVGgVkKMEDyqQq0ZnBDGiApMN5XbOyWthWNK1JxIqbDOFvaLE7x4Dk8nzvMbYpx4+cIxDCMh7BinERD2N5Ew+GbsE2sqrEWptXI6LKQ0c3M7cXt7T/COvJxZc0LUsRsTToSnw8yyJG5uJl6+ukUEHAtCpuZK0gURM1bnHMqAuEDOipwKa6ocjo6cK3UtHE5PqFZIA6wDwQfmoxKi5/5uz/3tDofiMIN13sLtWCFEj4ogPiAuUCusuVqIr1C1mqGrggjTEInDSEqJ8/lMVUtV8I7oPU4EKszLmZwTQwzsxgHvhOADglCrGbsgeA/OOb5x/zEf/vFX/OjhC37w5rO/bcb+7wB/TER+EzPy/zLw53+J/f0du+3Ggd/85sfc7SbEO5y3VV+c/VSRLU/rOe0lB5WeAj+PykW4udnz7W9/gxACqko1y8VJy9icItXCRCdQq+CouNp2LyAOUPsMVQENUARqRUuxF+GaN7JbG3U48ThXiSEwThEnjnUooErJ4HyLFNpxaxVKEQRlPidKFs7nhem8gPN4GYnBMY4D0zSiLNRDIZfM4itFlRAdaa0Q2rHiyQXO5xVV5e3DidNpZV4KRR3eCSqK3aYXw6KwGZp3Cl4ZoiIC+53n7nYkl8x5yeQCmqWdGyjJFtCzS1DBO2EIDu/MOINzuCjsb3eUopQKRaFUxbXoqeSW76OIqF0ETWh1aM2IVou+2j3gEDwORIk+4jGcwovhFqjhBbVdLbuW1bCJjlf0e+KX2H5hY1fVLCL/VeD/DHjgX1LV/88veTx/R27ffPWCf+7P/mf5e/7wrzPsJobdHgkBdnsIAfUenAfncD7YDem83QQiqLR8VDAfIoAI3nu++c1v0Nyz3dhXOI+BOA2A0grUtiioeW4UKVchvGKJMmwhJqgdCw7VADU2zzGACjc3niCBdclQCsvZwsdaLHUoxQy9FkdeAxlY5wPOeRRHKZVpt+fVR7eMPvDq5R05O754/cAPPv2UeZ5hLiCFlAr73Q3DEBmiJ/jAec6cjm9Ja+Zvfe8tb96eudlPvHx5xzRGvvXNl9zf7cGWKTtPpVAl4UWZAmhQQjRAbTeN3N+/YlkSP/qRMM8ruXrS6qE61oOBak9vDmRNDEPk1Qd3DGPk9iZwux8YR8f9hy8REZ4eDxyPJwMdpVBqpZREKhlxYOu+UGslrys1V6RUnIJzwSIRIIrDiWO/i20xV8CiAy2Zkit4QbyzBUQL4gq1Xe9a688P4byz/VI5u6r+q8C/+ksew69sM2TXNyTzcmo25LTlZtebVkVbGNdft3np9poXNzv+yLe/wZ/4je8w3ewZb2/N2G9uIUTUBwgBxOFCQJxrxh9ajudQscur/TOceX9DwK+Oyhb6Z6u4XmGx17+J9r+8cxt0t395or2leXl1iDic8/gAw2i7iIOjFkeIjhAsrKzaMQJ7nyqkUkCUZVmZzwvORcMbvJ3/sRmzayB7qRXVQk6Zdc2A4CXgxFGyIfnrkjieEk/HlVIdzs2sU+XVy8puvKQ2lltXxFXEgxdFBaI0oxgcSsQJjDFQUkWdULDvUotSq7KkwpJXSobdTUHxjKNSVPHiGKcB5xzzMuNXi958Bi1qny1lqyaIKELZogdRW4ydavtby7gEovN451CtbX3uHvxyGZVWkdDL1f0xt+7Pvf0HDtB9ldtvfusb/IN/zx9nNw6kJZFzZoiRaRztpssZ7WdWCzln3r5+zfk8s9uN3NzsLWcLlhOGEAgh8s2PXvEb3/0W+xf3+GlCdjvEB4iDGbr34M3Yt5/N0/eQfltI4BL6w3YB5Qpve9dMRcQcdjXgTpr7lw7MXf/sC5VzlqfXSi0FrQWtgjJY2B1AJCNSCb4QhgwoOSX2dws3T7OBYouVoULMeF/IqXI+Z2qB0+PMOlfieObxbcKHQKpCqY7728h//E/+XeRa+PyLL3h4eiQX5dMfvAaEaRyJbVHY7wdUBu5eDoSp2IJSlXxW/tpf/yGihd1u4P5mxzhGvvmtl9ze7sFlcNnKbWWm1EItFamVIMqL2xv2w45HXXk4zYCVGWu1UmNgoqzw+aePiBMeXwT2t5H97cS3wocMY4QI+/uRlDPEQilCnBwpDUgL0EGoWdDqqF4pUppjMeN3ZMp6Qp1DR8MZBEWlghg+IOIQJzhv1697cuchBMcwOLudfontP1TG/p1PPuTP/Cf/Pl7d3XA6nFiXhd1ux4u7O0SEvMyUnA3MqoV1mfndv/nbPDy85cWLez766BUhBHbTZB5qHJmmHbubPb/2rU8Y727MDQ6TGXKIZujuEsZv4btzWxj/bqRw7Xkvmb3l5dccJ2nv3fI/eb4Q0CsxV+XaDSvo9VqxPFVLzwgjSLDDlID3FUJhqIUhQi2ZaR/Y783rzqeeoya0FNYlU9OJpIXzcWV5s+D8kdefHfDec/Pilt3NDXcvb/n2r38b5x1/47d+m+//wPH69YHv/96PWNfCtNsT48j9/Q1xuMGHwO19ZH/vOZ1mHh8OLPPCD3/wGYfHB169uOVbH7/g7nbPqw8+4P5+D24FWVDN1FLJJaO5Gigpwv3Nnjo58vmRgz9Ta+cYCKIBhyelxNPbJ0rNPJ09453jfr5h/2rHXibGAabdQMgCfqUUYShCLVh1o0SoQl4qJSnVVTLO0q3GZUALJSXUiZ3+drEEu0VC9DgviBNL/1VZU0UrOO+IoyNGj7hfLmv/yo1dRPj1X/smv/atTxA6qgm1FvO6YKgyLU9Vq11uZIgtRW15jLZVsCq/+e1GIqmVIUaC9wzByk9KbV69orVQ0kLOCedgiJ4YHSHYSY1DaMDVyG4/Me4mC899M2gRu1RakcoWpv+4S9Gf0yuD38o39LDvEqa9m4I8e5M0996JL+6S4KsaMcNy+ct7DFH22/nskY1Iu3kasl/t4mwLiogiTgnBcuUYIUYDuobRUpW6pREO1ML+dUmonPDRcT4d8cHjveP29oZ5rgzDiGpGq5XIljVzPC34UAzTEEVVGMcREWEaJ9K4Ii4wr4qbM28ezoiPTDvY7X0jtAQr0dHTDo8PFnXd7Pe8eAHrWoFEWispCSmprdnBI9XSQHDkUnl8PLCuC7vJM40WIZXaQdBLWiTt2jrxhoNqByAVttJeRVUQAe8rImnDTDu847wz8o13qAqKlfF89MTg7Rjl95mxh+D5z/1n/hR/7r/4X8ABaV0buDGT02o3ZEl2gsqKlsQQI3e3N3jnKMXyrpwry7JSS2VZMmkt+OYFl3nh/vaOaZzI68pyPqO1UPOCNo8+nw7knHFemXaRaYoMQyDGwLQficPA7e0td3cvGKaJMI2WlzckHqAdDNIIEM/8bk+8303A5ZqjdvW02rMXM9ft9RdD72F6v4laKFBLo5W9s1NniLcfR1DIaaUsM4LgXGw1+4K4TCnZPFK1FUOcVZf9ZEDd/gzrLAyDlYlyVsYzLAvkrJwXpRTl8eFIfvPA8XTCRWWYBoZh4tvf/ibOTXz66ZnTaeV0SsznQqkzay44HwjjLT5M7KaBly9fUnJhnReGOJBL5fUh8zQv1L/5OTc/OvDNb9zzh777Ac55pGa8OrQmKAnnAuO0x/vIGO54eS+czys/+MEXnM8Lh0OiHhII7PajlTUHwXlY5sLv/M73Eae8vN9xezsyxMjtfof3nuaDmtFLYwQGAh71lRo8ghJ6JkcBtTRJNaO6bgGfiOBjxHtbnEK0fcYaUIUQAn4YmM6jset+ie0rNXbnhNubPd/85CP+yB/6Dk5gXRZqLaRlJq8LqqUZe6GmhZpXpnHg5d0t3ntKhlqVlArzeaWUyvm8ktbM+bzw+Pb4jBpZGzWy1to8QKVWy9dLuaJuOmc/vbMT7107+QEfvFE1r8PvThkwNMV+/ykLr3nb5wDgRpe8QufkxxAjn68X/fMBba+W56++3oPYiceqVu1z+wKy7cj9GK+hm3dXFO+N/IEqMdr3LxnzdlRYrFKQc2XNmXVZmc8zinIzTAzDwDAMjMNITnCWQikZckEWwXmlkvHVcBbnHATsfeNEXVbKUtAMx3OiKtzf71iTmgMt5nW1Ns+r4MSYaEMM2K1upcFSCiFWfMhQHUEcFUEs/abUwrIuQGUIVvOuBaZhMvS8ts9BEO3XzdmjuWvz4vZeC7EsKitFqVovxu4E5+w8i9MLzOMsivLe4UVwPSX8Jbav1Ni/+clH/HP/1J/j7/6P/CbrfDbHV62260WQGFH14ATVylpy45TYnWnBc0WoeFGCl+al7DzUWliWMygcT9FCr5wp/f3O9i0+G1kCzBCqw8fIuNsRY2ScDDxyzpFLhuwpJeNKMSDFNzaLb/l59/g9Sb523T/r+mz59qWu3UO/XnqT/txm2Pr8cXWOLh95De92r69mRO2ztKcNDaV3LhCC4p030kqtKAWlMoyeu/sdJSvjYDft42NCXEaoaF2oRQneE8IeqvD5Z4+E6PmwRFRHghv5tW9/2xbn3/4eh8MJTZ4irdy0PIEcmc8TaT3jnScOEx98tOd4niEcUa3kCsc58aPPH6hlJXiIIeNF8R6iF5yrrOmE9wnndjhvi/aLl3t2+8juNnH3KpFL4TTP5FJJJbNmWwDqYmH0Y86cHmeGWDjeOYIP7Hc7xmHEiSN6K2VKwVYEql0zUVKu5KKIVJwrdmsETxBvsI5Ynh5ibE4m4GJsC28D/oqyLMnSo7/T6bLX24evXvLn/7E/Q55PpMWM3V9hWMYRdxal1koSd2UDdvN2YxdRvDOrcs4MTLWQ0kKtyjwP9NrzlhuJ7V+8x/mW6zkD03wIDONEjJE4DMQhIk7IpSC1bIg26hu5ox18B+euwbgrUO7n3rZOD90aKbqnNm/ekvwrY948+Xay3l0MrIYmGNDX34X2dzaijfMNI/EbIFjVbt4YHXIzUAsMwYw950rOmZwV1UQtShx2+DCSSuLhzQFxwrh7yThlvEQ++ehj5jnx/R98bvsugq72HUs5UrWSlpmSVoZh4ONPvsHN7S0STqxZyCWzrifqWnj99sD5+ETwcLPzxCDsxsh+Z1TbnBecy0y7wLSjYQc7Sh2YcuYmZdaciAchpczxBHqqhqwnISdYTwXVQoyF+eiJMfDq5Qh3nug9IRqvQrdmoys+RM0gFecUL0b6GXxoTL1ethNCNAzEh2DYUMcAENaSrbKUMrX+crW3rzhnb0wgZzeWarVQrnkc69Cq5JTRWoghEG5uGIPfGgNKKeSUWNfC6bRSakNXafmPc1bPDIFxiNbxlLN1eNXcFoSVlBO1XOipIUZ2ux1xiIy7iRAC4mxRcCEgDaAT35D2zdDdVjPfVpWftHW0/Cpsv060r8zwHaNlK7dthv5sAfxJPVHagoQOErWFQ1tHl2pje9VW9+2LihF+LC21JhC8McGKKBoyiDIMnnEMlAo3NxPDUKnqLKyn1+aFdU4cns54PxDjgPeO+/s7Pv74I5Y183henjV5lFpbPd6xpsyQjGseB48rSi1CVhBxVIzhNq/K2jrVKor3rWbuK7iCuJWqlXmZybWQaiHVTK61VUwdQ4zoZBFOWiFnIwLl1uBSi5K0cDrNUI0/X8YR52RLPUV0K5E5p+AszagtAkXAVWnhu9lDaQ7LqxmkGbvdKinZuVjX8ix6+0W2rxygM2fqkRjJObPMZ2qtTGNkcIFSC+fTCa2VD17d8eLuxkCwvFJLIS2J0/HE8XTms8/eUKtyd/+KabohOMc0RFDh7mbPzc0tyzxzPCRqzcznoxn6OjOfTw2VVrz37G/2vProQ4YhEsfBUFHsRgrDgJ9G3DRaHd0HM/QYL+U2B5f4/SqOf5ZwvwPN6fUvW5lhI8uIftmwnxv8ZUGQd735VQhfe2TS9qu0Ska1mrTUXoe3/TsfGOJIdcY3r1Ri8LhojDnRhVIKN7cj4j3TruL9RFqVh8eZw3FFqDgCWuHx7YnTMbO/ueOjT26IMfLr3/01Pv7kYz797Av++r//28xL3r5fToVDnolrYbefUY04X7m9jZRiKceyWKRWJVBq5Xi0+2McC7uxELxysy/EoOzTTM5KLoXD+UgqCfWKOot0fLAQP4aRm70nJ2U/JkquHE8z53kl58z5fEZrYj4tRtoZI3e3e6P11gVV4xp0zCHEaDm394RouIhLVk9HLulniOY7QhTG0V4XnOEip3Pm6TBzPC3k/PsojNfuaeACUkG7wbspXEpY3lmO1I1OVSm5kFIirYmUVmN5FctrnbjWVIDljt6RRLbct5RMzolSSqOfYuCHM08WYySEiA+XMF/Vcv3No7dH58PLVfiu7xr6l2A1rgz8+jnl+aL9fAXvhrylD9cv3vCML51seoC/sbG+FOJf/taPQWtjfDlnoX/Lp3vbpS3WHTwSYjQEfxwFJ4oPjVEmHW6Ekgq1JoahgaLiGIaIC57d00gMnlIctTWaWERiTDfzrpkoEOwiX8BU8YgEaq2Umsml4pLipFICxGRlypQrKVtH3ZKMbEVQJGDhczN6J43urJVhgOIs7y7FzsnqHEUVrZmsFedaNckLYAQlSiE7Zzx659qZdq2GLlQRpJXhavuJKLUBoc4ZeKfOwD7TG6hXfPxffPvqPXstVgJazwjKbow4bAUUJ0zDwO7DDwFFaubp4cG4w+tCyYkvvnjNw9sHVGGIIyJWg0eVaRgYPvzIcqM4NCyrUPJKTivz+cQyz3gvTNOIE2EY7LOn3WR5vyi1B9Te2w0QozHmmkdXcQb2XRu3/GRDv/r2X36+KzFcCATvguu2t2um3LtG+4yJ055Ct7p6rXnjM3QQwzlrzKham5BFMW53zThVnAvWsRUL1ZXWtGFkkZ6p+OAYMDS5aiGlynl1pCy4BRaroFJypebCkRPwqRGXbvcM08iLu4E//Ic+Zp4XPv3sNY+HI855nB8Q5zifnpjnE9MUuLkdcE7YjTv2uz0hjMSwJ+XMF6/fMJ9n1mKAWgwe8AwRSl0t/auFh1MilUKMtlAJFScrYIuVSAUVLsTIgdub0Co4O2qtzPOZdV0s0kwHShE+/PAV9/e3LMvC09ORNSUjxogwDhM3bkS0I/aXXglQ6mwCIYKx/JxA9Nack9bCMifO5/T7LWfHPGxOpHUheMd+avXDdgOH4LnZTTgRHt++5ng4UTdjzzw9PvHw9oEYR/Y39wQf8OJAMWrsfmp1YKNFmkdP5JxYl4Vlnpmmgbgb8N4zTaP1Nw+xc0Oo0pFSZ6h9CODCFRDXSDTPwLifYOg/pqR1CfHfMeDt0VDyLRTv/9PLwrCtApdfn3+KbuBa/9lfLkgj1Ihl12r5bcqZWjKxRToW8RiHvWvYuJ54QlugtRm74gNMkzDPQjXHZpFXNWWcuczknPDBEwbHtIvc7ALf+uQl87JwOj5xPik+CnGIVIXTyZpQSh4J4YYQI3e7O8ZxJMY903TLsiYOx5WUYFlPHE+rEaqGkaqNn6CFVCqHOZNKZVd9X/egZvtuXhoMY1RpEWEcg1WK2uVVVZ6eHOez43w+8/Y8IyLs9xMffvgBD49PPDweyLmQS6GqAIFxJ3afVreBpIqdn5QKpRRKTuS0IAJjcAQnmy9Y1vL7y9iNQpiIwTPe7K1JX65Nw+SI1mVBVFmXlZwSaV2Zj0/klMmp4J0nbLmRUR7XJbOfduzHPQ4h1YW8JtKysMwLKa2A3aAxBsZxJATPbm/ltmEczbidu4TmzuP8c+bcFsqLBzEvb4SXVhF49o1/QltiZwjaSfnyY/vrlRe/8ujaO6Dk+n3NmK8XguvzurESravNi0Ut3ns0WOqTnbENpUsnOYyF1vL7WizMNnDJBB20WujpvYX20y5ymxXnK8tSWJOic20yUJCWTCmedZ5ZR+OOTqOBdi9fvUAFvB+Jw55SK69FOZ9mHMp8XAihEv2EFoeOiSBG451igN1EzYm5LVRri1RSEpYViipLsnZbaqWkhBPHECxq8cETQkRVSSlhrcWt393JpqYTvLDbWUtvbBHp3f0t0zRRq/Lxxx+TUuY0J9Y1I+KMZCSOYZzwIbZmKQvVQ3B4r9SQiWFAUHyrOsU4EMPAKor3v5y5frXGXitpnXl5t+fF7UtqypwPB9NIazdozYnD6YiWyvl0YJlnzscjn//oU3JKeGeo6TSM7Hc7QHj9xVueDic+fPWKj159gHOOw+PK6Xjk+PTE0+MDpRScKMMY2e133N/fEmLk9u6WYRzZ39zgQjTDbsYtIeCG8Yoq6zcPL85fgDqgswAu208K47u31uao61Zqu4Tw16+5LsN1T13YcvjmnqS3x6olId24L5/bDdZy5hDM2CVEvDiKSxY9YUgwYt1ffrJS43w+W5iv1Sojobnt0sp5WvFBeCl79jd7joeM1oVlKaBzE8XInOcFRJimCFT2t3teffTSzpj3fPTxh20hH0gp89t/s/BGMvOcefxiwflAzZFpUvY3gm+e8n6342434bSyzGdKKRyOR4pWECvZWgPQYIt5Y9rFGHhxe8sQPeMUGYcda1o5Ho1hqXVFayZ4xzga022/33M/3VjTVIx459nf3jGNO27v7/nok29QcuWzz9/wdDjx9uGJH3z6I1SFV68+Yrc30lYYrOFqHAcz5KYTqLWQlyO1ZG5v7njx4gPcw8QwTL+U/X2lxt4j3k1Yz/UOruat1G7GkjK1XFhuKWfSaqG4H0arRzp3ZRO2Ul+cokkDlfZ+bSoucsWU8974xjFGu2CNJSdNGNBEBd323FZHb4GwPoMS5RJpC+1vz7cvgSvPPPizP2w/5fqZDrJdefzemvulaODZZ1we/b9rUu6F8eWuHpcUwW1/v7xLnFjLpjqqGFuxX9cQ7FylAYYhoVVb30ELSdVy4pIzec0NXLWUaRgGKpc22dU7dlNkHiMlAZrRUimpkFwmhUwaU0O+/dZDMYRAEsMMSim9/mABWGOpaVE0V5w0gYpq4iDGwrPUo/dcdCGJWusVCdJSHcN8Wtsquh1Dcco4Dqwpb8o6ndFcq7HlarGKQFD7XAMc7XxrI+v4MOB9xPtOtvnFt6/U2L33vLq/R2rm8e1bai6UZaYW46undWmckSZndDxyPh1ZzmdyztQK47Tj9uaGUiqHpydUYRpGdh/tmKaJZV3QWjmdjhxPB0pZGccIqsQGxu13Rt+MMTKOE+M0Mk72E+cQbyU1P4z4cTARgi4AsTXBNK+s0OhQwHPT7en0cyRe2xXXy+9Xr3+en18ZqlpPuL2uK5dcG7de7eXyntoiAe3RQBet0caOq32hNeTdOY9rISRgnlG1hdeOKuZN60YUsYXVFF0V34AxC6MT6yrEceL+fuDwtLTcVFmXTCknK9Dt9oTgUecsFw+eMXiG4PnOt77BRy9f8vkXB0TfkHMlzTPreWY9HVmOlo7d3Jkoxhgj3/rGJyzryqdffM68LMaMKxknnugD3nmKBckgjnkVUlFUFlLGzpVaI1UYJ0KgOSJT0D2dV9a1EGMg5WwO5LSYPoD3xDCACDF6Xr64Z5ombu/uyLlyPCdSqizzyiHPgOD9ESeecRy42e/w3rHbvyB4E8x6PM48HY3l98tsP9PYReRfAv4M8CNV/Y+15z4A/lfAbwC/DfzjqvrmZ+3LO+Fmv+P89MD5eGxhoHW7LbPVvq3G6FFV1mVhPp9Zl4XSJINDiEy7PfN55vB4RFV58eIVu52FVTlZaW1dZtZ1ptZCbB1D4xgtRBxi61W3xpdu+CG0sNyHjVVn+ZVvebzl5pt9mrJD6z57Bj4AF0NXWi59FXlcQvMfi65deezulZtBcomQnsUPGxvusg/lEvpvAJ1cSnn1KkXYjL0hxfaSSu2gIL0rDNQLDdnbjqCTpJz32+/7G0ccFO8HdjuLKN6+CaxazDunFRdXptNqZKb9QIie6J0h5er58NULyl1Fa+Dhzcw8J5bzkXlJ5MWRlrNdO+8QVYbdxN3NHfOy8HAwoKzn6NByc2eMQQyjI2UxWiuZUoyZOUaPKeh6hsFTcmaej9ZItSZWEjGbdoHl8obo+9Ya7b1nN90Sp5HdbuL2/p6UCt/7/ucsy8Fy+vPaLr+h9Lc3N62K5BjGPdM4WNPO8cR5+WrQ+P8Z8D8E/udXz/0F4P+iqv9imwTzF4D/1s/akSqUnKglt0chzTPaQu0YwsZnr8XINYenJwRhtzNhCec8KWcUGKcJcY67ly+5u7vnfDzx8Po1aU3GlMppSw+stjswTiPTNDKOAyHGRnzweB8MjBJH3erol9D2ErHLVnbrt7pspbcvB+U/bbNc95KfW7qBGegWbl8Qeq4+QfUK6Ncvpwmmvd4MuZ+D7Vh5Btj111ny754vHB03EKtJbzX/vuA43erGRgOw43ZOGUdpIa5nGh21CPd3K8tSOK+QMlAr8+nMmlbWvOCjJwCx8R+mYUfwgdv9xDc+esG8mBzV6bS0E2DNS+uyUHIhl0pVyLUwDgMAQ04MOVm//W5P8J51LSyrRTa5ZOu8zCBSKWL96k6gaqSU0BZMq8b4YAuGb9wLxUQj7f4UYyRWSMm6LKtamlBKJfrKfvIMnbFXoVRLHbwTzueZZVlZGz615sKyJA7nlZvwER/fVE7pkeP69ue8297D2FX13xSR33jn6T8L/Kfb738J+Dd4L2NvrayrdbOlZeXp4YGSMze7HftpJK2Jw/nEuiQe3r7l888/4+72jm9/+zsMQ7Qut3kh+MDd/QviMPDNX/s2rz78iN/7nd/lb/z1f4/5ZOW6Wuvl5vPCze2eu7tbC993E94HxnEgjoPx4eOIipARimJ02c5974YtVo4D2fpLthIcP8fpb9ZxPTCgFKu3Om0U2L7b5kEvAXvP1ekv6NeKZyF8qZefbXBCf3lVwzG0WP66rR7OW/9/W3AspLUmDh88UpTiClrsnFpBwNKKLtEEhRCU/d56Gxx7hJFpHFnPwvlcePMwczjZwv/w9sEW0QDixSwjmSbBd7/7HXYv9nzw0vHiZmJZEneT4+npyLJWzrMNijg8Hkm5MN3s2C8Lzntu93vu725ZcyalZuw3NwQfOBxnjseZNSWeDsaQo2ZKknb+7DuPy8QwDoTQgTSTrBrHASioZgDiMDZ6dqbmlZozS0rM281vp3gXYLiJBvTKQFVhma1h5niaeXx4JOfC8XS24R0NDFaUD6c/zMvh1/n+41/nnB4bUPv+2y+as39DVX/Qfv8h8I2f9MJr3fjvfOtjuiBF9zbPwCW99jRNZAHZ6p7eR2pd6YqbcRwYoiGZ3WisMSObkTfQqDPrgvetb9h+On8B5J7VzFUu5afrv9k34rlX/3GbttD9x/5pQ9w78NbBtovu2DUyf3Uur/bRy3w9Pdimmlwx0K757vTP2kr8esHueJfBd/mYqwtpb5Xnr5BWCeg19V6d7O2ZqrQ6vSMGayQpxXjlMRQyVhJTlJpt8aFUNFk3ZE7Way8oQ7RGnd0UyCninN1DKRfmJVGqgYVaLbUy3TfBi1DaT7eBieZJrQ3VoU3N1rWyfG3Lq3l8MyofbAEuVVr9XOiiFJ1L0KfKoGzKONu5VHMW3lvpVrz1rJdgn+Ua466qknJhTQnxtqgiQpAR7we8iz/mxvrZ2y8N0Kmq/jQ9+Gvd+D/5J/6oSpM41pzxwP3tjamY5szpeDQEPmeoyosXL5mmHeM4MQwjzntKNeXO3f6GTz75hBAi63zmh9878fbN61ZaMpGF4B3jMLDf7wghsL+5aei7eXLXut9wjoqy5mJNOtEINxIiSGyLQK+1t/ZW4CIxs33bZyH3NWT27HXPjEyb7HNtyjuXvPxnnPjLrtTev7HmtFJKoeYGzF0vHD3v04YztAMTaYuMtAddCsuimp7rSwf2RLHEveC8EgdTWHHONNJLazCptcszJZwr3O6EwXvARCrWqpxypdTK4XRmWRNSK67p5D+++YK8nJmmyO3NiIjy8tXEza0tGimbeMbDIRnxRB1VjdY6z9Zgk2shlYwTR1qWhj0IwVvNfD/cAmydaGbgFhmel8QyryziOM5Wthx3hWHIxCDsdwEnyuHpiZIT0zBwf2v4kZbW/abaGn2aaEjnaKgz2Mc7KwvvJm4VUi5U51nXhLgAPlon53lp3W+/GCr/ixr7pyLyLVX9gYh8C/jR+75ROmhUTZ0zjgOCcHg6sK5Ga6zFSCO7acdu2uE6UCbtZnJqSjJ3dwQf+OLzz3l6euJ8PBq3WiyHGobAbrfj/v6ugXE9P++e3W+eXdW6rXpZ0PvnjLlnj2uv3ok0emXhz3Leq1e/4xWvgbqql060LkDTjewnbf1zr7nvnS1nNNmygWsi7yw6ejnmnm83mH57zkIHtx26LUJ62ZFYO6c4E7eAPtPMIdVq77UqqULVjJPKGB0OKNURgjJnhbWyttC15mLNOVqoKOfTsc2qm9hNZoy7XWC3i5agqZAzxLGwrHUL7VPOnOYTa1opWsmtq84YasIwxq1sNg1j87b2RWtV1tWA3mXNFl2okFsCtRYhRGU3RWKIOAeH48JyPnJ3c8N+d2eqNWoLR61KLnaCw+BxEtuN0+4MZ6lgiIFhmnC5MCVT7zFuRyTnyjxnq6z8hHjyZ22/qLH/K8A/CfyL7ef//n3epFpZu+gjrV11WTY0PqWVa2lnHwKuyfXEwcgQ025nq+swMM8zqsrj0yOPD4/M89lq6C6adtxoyrIxxta8YWBMkKEJBlg/sm+U2M6Wk+0kX7WvblZ9vf345tLN5+rz113Qc7167aVBpS8eFhpfY+3PP2P722agbAMQt8iipUAWfpuSygXdh03LThp1Vmijnpx1yIHdjGocYmn7ccERh6YZqA6lgaAYgCF9iKEDiC1SUYoodayMu4oPShWj18ZsDLJcwOue8xTxVGJTc9k6x8icT08bBwJxptLqI7kqSRNJKy4G9nEgl0DxhTENLGtiXhv/vS3upmnYJbVbf3lTKFKFGEPTO/CM045clXNS6nZZKzmtPB1WHEpOK6iyroW3b0+G9dSmDl9tyAQIEhIi1dLEtsD0nwWQaCqycTciMYAElEgIBhDmKfE6TfDw8xv8+5Te/pcYGPeRiPwe8M9jRv4vi8g/DfwO8I+/z4fVUpmPR0pKAOScOTw8UFq5rLO7fCt1DePAOE52EQYrZ9zd3bPb3zCfTzy8fsO6Lnz22WcG8qjaxFDnuLu7Zb+3vvQxWo6zts+ZUOI4tEVkNCMPEfGDNb+E8LyV9eLX6JJHV2do++1ZKa2H6fCOoctmoO1NW17X80VxcvHEXO3Trkfrlxb6nacqV4Z+yfddR6sxLf3rElzTpUYw4Umh3XRqLaZlWxNcW4QCIh7vK6M3dDrnmVLERlORQG1iqXeCEBiinavkEzlYJJdTpaRKHCCtQqlCzp5aPS9vRlJxRCqT2LHOKZNr4bTMPL45WvU/jOA8YbCBHaUqc51ZNbPf33Nze2NCGvtIyoXD4Yw7HAHBSUTEeu6NDnsx8mGMxCYk4ZpI5939Pakoa8o8Hhfb3/HEebZRVcenI2hlGgIxeM6nlcPjoy2SEoHQIGLz9IUFRXFRCKMJTE77SIjm1PwQcBrYhdB48R5KRBX2e8MQPptvkR/xzn34s7f3QeP/3E/405/++T5q2x9bnmhPbDf7uyNujO3WhfiC9cE7Rx85nHIipdTyocugh67S6duMrS62bx7TNfEM1zzQFUjX+e9XI3nbgfVfro7u6vdrhwmX4Q3X2NiV537HTz//fcMC5fKe7WXXq8TVc40BZ95VtncaaNnPq3W5XdaYS67+7Ci2IOZyTbT93CIccXTVm6tQBJ49x7bAbdekaX5oYyRrUFyxHKKKMAQD0KI4hpZaFAVy0wrpPS3bWdDW3moy0v1hVY1+/9A478HOjYsIjqpNPx5L4RptYDv2LixBE5VwXlhLwWchZU+pjixCbUzv0MRScnbU6tEG4vX1t7SItaBtZh9kac1EUUxwAwgNEK7aWZmyBWQ9Ktm4ED/n9pXTZYMXapsmKmo5dYmRXg+upZJW8xJDjFYqGQZ2t7eA8PbtA59++iNyWjmfTkaaGSIvXr0gr4nldLIykbcLXHLmuFiettvtGKfINE7EMOCCNyzABwvdQ7gSo/ANnGqtcM+Mv/28zn/ruyn5O4bZ/iXXsLcI4qW1jjYU+QqRF6QLmELZiLLU0ioNztn7neniqSp1tdruFu7SeOEolbTNjuvgoGJ69de5f62VorVpDLQa+hajNFygKqX2+elAG4+4LU+b3DJWh2+Elj6xR2oluErJBdFMFZASbMYbShADHKPPCJa/jrsXVIRVPUUdqarV51Pm8PjIeVk5HRceH484H5mme7w3ddvbm4jiqDrSx1GnsqJY9CC5UilUJ3h1uGDYzb7pEeaSubk14PF0FuYlsi4rh0cL+1/cf8h+d0dalePRBms8Pa3Mc2ZNhSXlNhTSgMeyZMphRRwMh4CLjhAtXbVBJRPeeWpy6GrnbpgMH9D685Xc+va3RTe+63NrtVKM2xAiTJhiSYAJH/aOtN1uhwLrjz7j4eHBhCiSvW4IniFOrMB6ts+x0TyOjAkMiHMbGh9C3JheJkxxGfJw4cE3IK7nxc3lXWfb9uzlpr5Koa8gvGv33iKMq2VBRMA7pHZJJ1s5VHm2p+1jKltk73wTz/BqEU+tqLOpN078RbccK3faHHDb0TPtwquy3bMHve5g32P7r4GJ3ftfEAfh2ZK3uWDZ/rsIX4BrXXve2cKiYuozppquqCheKni7FwZv3Pm5OFIFXTJz64xcW3fjuhbOcyLGkRhv8B4TNBkjVT2ljA2tbxGYlk0azRerAvTIRsWGUe52gVrFevtrZRgKaxLms0NqRlV48eKe25tXLEvF+2yU2PVAygIZSrEItDTgMZXEkmYQZSkeH6y8HMdsJKSdI/iIrkKdLVINQZDgnpdTf47tKzb2Nno4J5uQUdXQ9eg2fjaA7u2WGQbjJ4sqaVns5nPCOA7UGih9+mlOrCmZUkkfj9tu6uA9u90OgJwSp1LwIXCnFdRZGVAxQoc0/qQzHjkOet2dJn5Ji0A68PXO19sMYDPyH4uj9BD/eT18q4t3z8tGuX8WI/TwXq8/akP2L1pz0j+j9fXXRk1G9Xn43j6ylu7Z2Tyztg8qFDqXvpLR5nntoxvBSE19rjfPbNHQl86BNYKgFs6HKKgXm2FeZFvoVG02mlMBZwM0qwrqBF9tIa4VvDhuph2injWpodbJcQwz6yAgERGTPJuXU5vMmilqyrlbKrJWsiohmD5d8FYaS6Vry9ni61xsdN4AL0x6y/vImm3wo/OVgHJzGwgRpsUxjEKpSsqJXCspeZZki7upIJlzciUg1VFmRV2hrJWytGlBdW269jO/iL3/belnX5eFvKw45xhCbB1BVmcOvbdchGk3EYOF/Ov5bAIJTtjf7NrNafXkp7dvmc+LIb8+bGQZMDR3GidqrTw9PTIvCyGazDSuUnNGKTgFz1Ut3Rl3uueoRhltA/kqDcVuAyOeWeJPMPJnDr55W7iU29r3v36hPPutRwmXhWDbr3LpOe/70faOJseltUDNaBNq8O6S01up34Y8WLcX0CfLtlCiaqHQSVDd0Ctd7rITSKraxGhrirmg+M9PhPWJa5uA6mjdZs6hxVmprFi04PCgAd0GZQo+G7AXxOOJLL6w7pXRJV6/PfL26QlxlZJO+FCIw544enIpPBzOpFyQYN4Sh7H2xLGUDEvGO4ih4rxwTon9PDAMRtn13hHCyOAEHYTbvVCrcjhV5sXSTx+s0vAyDqhG0lqZ55FalPOcGmEmc55HO++1D50UcrZzlVZF1aLXtKwgyulUQSqn0+H5DfWe21cexm/zthrbycbe+MsLNpZTByosh0zZQqjShROftSB2D9NEFLGbyG8TXa92D80jVKQxrX6yB+rg0/Nnf1wZ7RJ288zgv0Q3uvLo/bWX1tUvf3w38kst3Ax/+/Qrr37x7n3fW5CwBRO9nn6ZiipcDuXqve0AtnRE4aIa23j7ArTBCOIEqR2Ia3PHuQr+t3PSSn2I3eHO1GG0msdWLErY1LL7+W6Xog2LBbEFK3io1dh5Q1AbldQkyWutaLaJNzjToEvZjE1wOO0jm/p3MWMSUXKpLZtbqQpDqgi27xitiUpoeAuQcmZesuFFz+4XuwnsfLXBG6Ibn6NHbtJCItfWU9FOsOrDHrUBrL/46Oav2LMbKpmKMZrEO4bdRAxxY86ZOMWAiFByZZ5nlnXh8fFgMj/02mVnOek2s21dM+fDk+U+3/iY+7t7U5c9Hqi14n1gtzMyzbIkfFHCtNsaGi619Xce0pVpLjlpv4HNe+pVR1If6sD22u2fzeJ6yE77Htsr3PP3ABfDECxa0Wq6WbS6eDuxxsArF88OjbeuDWoWS921gXvemjlq6Ujx5f0CpkHXA/UNuLMJOp0E0oEsrWrlPTVpsCEaMLrMNu2nlEKppeXAAa2OUqSlbmYd9rUEzWb4NuTStOmrahuDrDiE6DzBOXwD/FJ0lLxjN1arOhBISXk6F9JyZlkzlZmiyjknslbq6ozy2jATu3LGFzAy0AooMZwJ3ib73uyMifny/o7bmz0xenaTo2rl08+PvH77RAyeaQxWgmyofk5tIGZV0lrJWUEdwQVULfKpYiVL72zxXZMx+IbJ40JEtZLLQqmZcP59gMYDG1OsaLUe6RAIg9XBBUPRh3HAieNUzuSSWdaV4+lknHffhgrWukkH0W5Q1cK62rw474x4k9O6UR9970wSRykFxMoqmzDFpv8ul+dENiVZfkzJ48uqrc/++GXkvofhV0DY9rz8eMactBxYkC9PbuWyeDzbX0fJr7z85ZempOqcVQBEr/ZzJUvVrsqXvPNVSU0an9u1tCkOJgZi+5tbWnAF+LmuCVANgW+DElUwXrxvSct2OjsiCZ3c47doy66ZE2EaIyKVZVe5WSqLLxxOSxOarKSaKQprRx+qkGurHjjPlpyoNQmlnFGtdL5kDIHjaD9VJ1Qr4+C2DO9wXHl4PDMOnlqtYSbYACIrE6fUHBOUrDgXLzV/bSzFVvKt1bQCECFERxzt3mbNSKnbuf55t6/W2Jt3iDG2IQ59aECguD5qSJquwyWwDSFye3vb6IvJLkSpjfutaLac1OO43VsL43w688Xnn7OuK+uyGkVyGLc213FnNNwQA+Ldlc6ce+fn81C+34Mdn75ISNjRXsi0z7dLPMCWZjx/QSPSSC9lXdXl241AB756/t57yjduADgJVwdwOTKrl5v0sn2dHsLXxobTNsb5EoZXVZOB1p4ute62rqiirj2nqLt8r+umIqEfM1vaZl8wIGJ1bqqgrskCuBbNiC0Qrt38VvduHrih6DjduP6T8WzI1ZF1YF4Lcy74GeZkU2c8hvarCEtSyHaW89VUVlUzXq3BSmTVUsa0wjKvOJcpeuR0VobouHmyCOjzNzMPx8Kwwloy3gkx9MEnNmhCq9pY5wpOCs5lbPqtfa44v12/OHoiHh8rcbA7zYeBUhzD0y9mtl+xbrxN2djvduynqfHXbWZWduZpLUTXC1FNTO55GAZqVV6/fsO6WAthbaFOzSY6GINnf3ePE+F0PHA+HrBdiIX2wer6u/2e3e2NGXi7+Jv2nLjnnPhNTfW67HbtWLvf66+6GPaPPwP2U64MoHfxdeiie+mO/YkhanYsVUHKxevVuh2rExORQKV1wzVxikrzHhV1pX0l125ubaUnG0SIb5gJAsWGHJZSGuDXaKrSyqVtIQJFfX22iG3n4drwpbP/zKC1Xo33UloDueBz2cJ4ol7l7LYQGn5jffTUgvNWrBuKM+7E6JkXU6eJs+BPhSIFFcfkTZ3GLZU6m/pryZ240s9Jl6GyAaI5Wb/GulrD6uGk7KYzMQr7nQGZj+fMaakMAXaz4QlD8AQvWyUEbVJUtQlZtgWyixbFGBmidQmO09AIZYUQbTpOVaHWwvi2d3m+p+G17SsP4/uwAQupPb15ozcMyJXhgP3SGXO1WJ6eUnpWRgreauXRmyCAcBHJsHr6VRsrHagyr2AlN/fMG/EuMHfthPVyYNJdbw8z333xNTrXMRZoU1QvBg+b8+vp+fM3vLs1sgxcADp9dlxtD91jibB16F2lFc9D83eO4xrV4/qYrh/v/r2/792tpSi0oRNc3nqNLXKlD9CFMp413tAMxbHhJSK1iWfYMEfvhRiEUp0pzFRlzTBkpQ9rUITozRi79lxRa12lzUZ3rRphs97biWvnsFQhVSAry2p1+ZRtgnduv9etrUJsEcG3hdHQR21p4kZCamH7s56rDUJq18LEdn5sqvc+21c8stkxTRPTNDGOI6rK3BthlpV1XQ3pHEzDqwNk6zzz8PDIuq48vHngeDjinSM2za+XL15ws99t/rfWwtPDA/OSGZ1jGsdNB9xmwa/MpxMuBIb9HX641oWXXijGgnJzRRdbkg1pthtS2o17pQRjKxRfuvGd/Vuwqt4G2vWHtPy0hdkWzbdXtdKauNZ6q2rCnNlINDY7WdsgAjNEaSw+J8WIgCrUajdxKcYluACEF5va9OY7WMcFQXeNd3Bh/F0h9N3Lq9X1O9jV4Y4uxgjSVHUbW69YObO0tEycECdbtENwTTHGSoi11pZ1W+tsP8XOKzhhsKnyeC98+HJiSWotqZNpGOY2D27wkV10lAqnxQx1SUpKkNXMvdCiKOomLKwIEh1ZnIHNsx3zkhypSFOkaQvS3sZTBe8YYruPQruO0scws6kEh+DxsYmiRsX7gncZL51kZo7R/+SO8p+6fbV0Wdpw+dZiWkrZHrlkSi242lhkV1FKqZXzfGZdV+b5zLLMJhw42ICJYYjc7PdbuGRiB2YgwCZaAbDRQVPaVtXrEU7ds+uz5VO2H82fPYsUZIu124u0/7jy3Jt3+NJeuZi9Xn3UVTLQgTc1z2h3f6vN6vbLFgjIdvKcDW68+oxewrso0ejl0PvCsomL9Pdcfddu7Ns+313UroDHK+BSmpdz3l+iG6dIaYQcUUq7PtaI4ja1Wuct70VMuto5q+VvffeIeXhslFPwPY/3OA+pihliqaxSKAXrLhNPLlCbR9ZirDlEydIWSriQtHyLu1t0UNX2pSq2n9pPrvmpXEyc03tvnHwBlYJuirxyiU5ojEjfvXsL811tf79KAX/e+L1tX62xO8c07QjB+nmv+4ZV2UL7okrNhafDgePhQGqIuqqy3++ZhonoPVMc8M5RUubtmzdm6E13ruTc5r35rYUxBE9sfe3DeKUHfx2+d2EKuEo84VpKmZ6l1+e5N1huLO0V/bX2L2m2fv08bGjzVYx9WTaky75sTL9aKz43QYquK+d6Cyu0u8/226Wn6oqQqTVTam73YzPmLdTU9rw2QKlsC6OqAWROnkcxG5p1ddCXKsNVxNBkbHpjk6nJtL57QEq9fDYmn+UGMywjyimFaiWzdi7FOXyPuhSobms8cRjd1gsEUaJUoqvWaDKapPOaHSFbCdB7RykwDmLik1k5zRZxyHG289a/G2Alg3aviJlQCIJvkZSIRTNrrlS1un5uoio9NellQxEITsCZsfstdLd9xAD70UBAGuEphi9xN99r+4rDeM9+f7Mlad3Yc07EOBDapIxSLRR/eHzk9eefA80rINze3DLGgeA8uzigtfLm9Re8PRyaFvmCADf7qanIuq3tMrYpMsMwMI6jjXXyrT6y1dO7h786cFt+N6/eE07tiWcXpUSwHu93Q3TL057l4l96XLz55XNbJ54qmi2sdlpBk3nxTroQ657q1Q47LmPM2c8ZJTXGYTOsXgrzJpNk+XNtC2UhrevzY+lrUyexwxbCX28W+suVYbTFpBl6jLGlU01xRaEYGkcVM2q8Iwx2HWqtUCFTSW3SbBcD9f3YFSQbVlmLksT04EMjoESpjK6iTpDGl1iSY80tty+RWh25eHJx5FyZTpWUK7kklmTc/dxFBzelog5YGpvPidXci/bQPjOvmeCFNVm1xAdzPNF7JmlDRZ27zB8J4Bs11zllHBw3+2hOohRqhTE6fhFr/8oBOmg3Wu013cuQRHMUlZryFoL7lmv7dlIvwB7Ms3V4LctqNfctF2pePAbLg1q7q3ddqOCdMU+bV+9b+/e7fxMuITUtityAuqvvt/3sXn9785X/fucN7TU9z97eX/USyvcqxYayN+99XY5rApGWN+ft3133r+foLdpsX6tHJXr5nP4C2b52+6WFmciGnvdcvYelF+073Q7rS6e4IyxytdyJYQO91Vg2AKtevUe38mAbVWHevNmfa4beF0BVtTFN4fmylJ0h4jjwTUKLhk2IwDDYPocIQ1CyQi5gGXxpGYq0SK7JcLdv0ifROnvJdn9c+xBjkRZUhdJUbIoYsGfHpA1/UhMEbVNthMp+HPn47iVzWnmaj+Tyfl1wX3md3WSiW25dK8MwEYKJ+i29xJGSeTE/8uqDT8x4m8BCTQXNyvF44PNPbSRUyStaMrtp5MXdDTF47m53TONgeuTTiPeBaQzE6PGxldl8b2P1WNmlldl8b3V1l7to+wraKLmtPLUl8fZTOzL+LDq4CuzbjbBhLP1OUKGR8a8ssW7a7ibGaGFsbmF6zQmtGcQiF1OLnaklo63ZCC2IrthgQ2VNXQutVSjUb2WcPh6qFitrWhZh36P3ZxvF0xhiJorh+xcHtF1bbW2Y3eD7wtF+b0QUhU32uaK40QY+uq7Tf9kD2sg3fXSVLSCWd/cqTqnaxnKrEW92nloFFyo+dHmo2ohd2So8VaguoSo2FdgNlArjZL0ChYq4yprBLZArnNeFZVHMwxvb04VK9N7IYmrRleXfJmoZYqeA291Qa+a8WBSastXjU3DkobHoRgvhF6mcteKdpRle4I98/E0+2P0pvnh64P/2N/4Knz+9eS/zex+lmu9imvHfaOf9L6rq/+AXGRRhF7dNEGk5aNeBy8VC0Fwq62rMuKGxsZxAaOHsWlay2tywx6cDaV3xYvnZ2IY/xBg22mZsD5vWYWHftbTRs8S8Gyn975fsuf+5/6LNXcn1l6N5x+tI4Hrf22uuPlX7a+TLr9Xm2VuZsC8mmwx0baOt2kRWtKKa0ZqoNaF1bc/Z63t506KRK9AN2TAIrVee/XIXXBYyuVbtZRMHsc/pN3JXxLlOaPT6VG7nofcFKNrYcJeU6HIurvESM3jXcAppZKLirI3Xi8OLnZOIozhhqEIp1ouOWA09ON1e56uhEM4HnDdhCZzRiMcBpsFuh6GAFGWVgmgFPAYrujbmwZiBrrFDnRie0mmw14FNVZNIs6vuUOdwGPNTHdRoZBvDoYo166iVDu93e26GgegDY3h/pdn38ewZ+G+o6v9DRO6Af1dE/jXgv8LPOSii1sL5fLJprNnG8fhggpNafRPKH7i9uWmX1QQNS8kcjjM5ZT7/9Ase3j4yn068ffMItXB/MxFGEyBM2ZoRSq10dNv7RraIAYnRcvVro0bMw19z46/iTkOt+7ewm8J+k4uxmtumywH39li7TVt0sIFnAlf72xaFLf7vYQLbw1RbnYXkvZmo1GbEuk09qSWhNTWDN10039hnroKjtkjAaMOiNG9et/6EWvqYKbZRzT0pETpC3TkT1glYc/PsrVmplAtPf6PhipBSpvc9dE9bqg126JLJAnRdLGl5vce3UFvbMbX/GnAafePWVwG1+nkqujXOBOeoOHI1bsc0BXZLoRRlXq3zLOVEKskCkApOlRc3yjTsSBlebJ4dliSkrJxmwzDudwO7Ng7q1Ka3lE2xt4DmbXVXLIUI3qS6xsFkzp0UnK4EEcYwMg6O/ei53Zvoy83OMKjazu8hL1uV6X2295Gl+gHwg/b7k4j8NeDX+AUGRdRqM9jW1TxzCJGbfcC5YFpb1Ubm7vcmxZvWIymdyUvh6fHMfJ75rd/+Ht//3qdQC1qSifYPA/udNRWknKHPH+vGHkwr3sWIi7Ep0vRk6orFsNXZO0LfI+pLPdrUbdtpq3bxLmGsrRlbPrs1tsglZu2rRl8ktjCeqwXg6n3V9ucacmvEk9KIIFbTrrWQ6UMfbOporSu1rG3NGlvIKxvRwzduPGDDErO1U/aqR1/qro3dcHDdPHrHQrSKab2roeyl9BC5PjN4ELzLgGyc+ZwLueM3rXJCFTN2pancAPhtKIUAz0rNgjXTOPOSTppCbLbPiMExDo2T70xRZ24TYVKunM6ZXCpPhzP5uCBVccXO+4ubHSHuKRXmZJdwyYFUPKdz5os3Z2pVPrgduJsG5iXxeLBFbMmZXE2dJutVFWTDHSyd2o+OGH0baroScExhZDd4bnaB29tADI7bm5EhhI1g9rTOJrf1ntvPlbOLTYb5e4F/m/ccFCFXQyK+/fErrgEW16moDZjpPOjj4YyinE8PLMuB+Tzz8OYNy7Iyn5c2+dNKdaG1yPYcdNsa0CPXufcWujcjbmHWcx58+3urs7b+MfvblYF2YYjLiqAbM86Mv4XW7WVbIqBcGfyWuG8h7RbtCs+ALtG++PTW3gvxxXGpa/coRN9ZSC4QwcUjPmPwXaUR/TOcCCpNqKPvTtn65U2foNeA9bL/d/a9YRbaWkeRTc5K+6e376ZV2wLXsRJtYXz/eYEArvZsy5BepwZcFVaaQo4IfaartHTEOzEhCmeDGIfoKcWKgKqGFYVGWHQNaIiiiLdQez9ZRLobPdNgKju5DJRSTa+uFHJtgyO1NwnrVg42CapLZOJxhOCIQayc16t8GJHJ1sAuAeb5eWSl39vYReQW+N8A/zVVfby+mKo/eVCEXg2J+Lv/rl9X55UoNi7ZuYjzESfepIMGz+HpyPf+1t/ifD7xxRc/4PHhC1JKnI8n8xLFvF2IkZvdRAiOaZwIIW75uI3wjYRhwA8DLprOnHpP9Q4VR2vBsFpnHMB5qrfwXltoX3suK9ZgInDJJ7+crJux9dpxvVyk7bWdcdbz8f52NcPu8kh2vkFrabPr7Ya1kDuxphmthZwWakmtrlyvhkfaoiVG+aIWC79pAJtlu+7KoMB6rG3hLLmQ12Qc+djaNb3Di7HmlrNxxPuCE0Ngv99vdXQrrxmtGVpej6dWjDHJJTc30R+PgbdK1ozHE6Rx/DddvouUVtMO2c6LqpKr8c5zhVSbqEaL3rzYdy1VWUv3tnbifRBu4ridmyFEciocTyulqjkTgFqQdYaqDGFi9Mpu57iNO8CxGwbGGMhl5MXdnqLKaVlZi6konZfZaOEUauMteN/LcK75Go/DWq7vbiJD9Ayx8TZUWbKSVEEDaCTpiOpzAPmnbe9l7CISMUP/X6jq/7Y9/QsNirCSq62yXSWz+S5Q6/19fHzi8PTE55+95s2bzyg5sy4zKIzDnhiteSaEaOh657+7i1fpcsDybo+69BZLu1W0qc1q8+x6/Wgeox05m3Iqzz3LZbvO7bvf14tn7V6/+aPLuy8LRUe5euvuZQBj91wGzNUmNWUyUVfetRs7F+/aJaO4ynOf4wbtHc3ro2bIVaRFF44L1qCbgEgfztlddC97XrPD+nc0xL/V+cEiL+lftx19C/ctTX8eGXSv3Xd5OXuyZUgVaT/NexpTpb/KSoY1N8HMtohLS0dEnPXhR8MEVm8jp7x00rStmlIVRzFtPBHiaJWDMXiCdwQv+OisZOYUn807K53q20C8ZuzSKinXGIj3Qozm2XsxSGkz5Ldv7iiN0/G+2/ug8QL8T4G/pqr/vas//Sv8nIMievdZKUrJsKwLT08HcqqcD4X5WDkcDnz/ez9gns8cnmy0LbWaljwgValrhhAYnGNw3jjyzhG9zbiO0fTg4zjiY6SrxfahAi4MSJyg/duIEZcBjlv/+rYk2GbmpI3LLBetNe031dUt2gxbW7j/bGTzs0vUL15DcS+x6OV31HC5ip2LhkDXS2vg1Z4cvWNC1duCkUobRWSLhYgjDDzri65Nt78bb8O66ZZUN0kq3dq0ai4NaHWtX9tKqKU/GrJvI6+9Mf62gKZ1mCEX7ZUN0PQt8rqKHsXC3Payq6sCiFJcQFGql+ch/XZVzJurBFR0g2Uuba3ahFNiAx3FIoWklFyIotxMNoYp5Uw+J8RHfDAdRStBeqpa74UBg8oQTDhyGFqU6GyR8d6M2QQ6FkrJxGALjveO3WT6i52NWBXmOVPUGc6RF754a8Ms33d7H8/+DwL/BPBXROT/1Z77b/MLDIoQsYF+qpVCZVkWfvTDzzmdFt5+ceLp7cw8L7x9+2B68GWmFmt3jMGMnaymo5YrgzgG55pqiRFphsH0woZxsDC+z1wXm7suPljYPu7ZaEtb66Zv+EE3nIvBbwbIxWNr7+DaGmeubsFqSPlW0uoA3nYyuHJV9rtobd68f2ZtJZ6rUpjq1k+e1W3GvnXWbx74QjgpaUWvZL2sX91bVaIf7jvG3gcg9mPUqq11XLfPKaWQU2rDH4zUlHPrd8h1E7D0zlq4LPLqi567GGU/K1s3n6VQl4VMG7gGF23ty5KpQHUe6yZr7cmtWtHTKmgRQ7/GIia+W5WUrDLgxBpWqvd4FwxQPiwsaUWccDMNVFUeH4/k+YwPI9E5HAF0bOfJ0iuFNrbMOjKdHxHXGHS+GXt01rR1LKxrYRw8+8mkpG1irCelzLKs1KIcl8KaK/NcOM+Z14+/YmNX1X+LZ8vos+3nGhShyiZqqAolV87nM6fjzHw+M8/LxpU3EMrCFRFppQkTPxAV4hAviipbF1bTX9f+E9CWn4qYd+0dYrU0kK1aCF/1KtG2Oq7da90V1YvnUd1Aq+tTc2kP2RLxJld8+XevRT937kItmTxbLl6bS+rCEkAL9aTl1moLQa1WIpKmrHRFR+v1cmrTy7syJG15rnYpratw2olDpTaGWj/Wa0IQm8F2gtElArlKB9rD/tSZddKXCluM5BraYzu+0gQd7I/tmPv1pC8OfYF4x/vT0g8qVUr7THtXffZeMelu7SKbbXmXDoqZik+OhZJyO2+Oqobuh+BbT77l4Tklo9xeiYZal15BsliVxglRPV6bY8Fy9XGYbM6BNzap3dc2gcegQsMb5qVyXivrWllSYcntXnnP7StXl13mZCODqil/fP7p5zw8PHE6FuZTphQlr6nd8A6IBB/YNTBuCNFG/3pv9W7x1OIoyVOCoxZPKY6ShZKbKKEEA9aaPJVULOxyHqIz4poAGWuwiB7UG8DjzEiq6+GtySA/W/2uXUwnkxSb9w0gtV5uXL2E9vYeu/Hy+cjj559bN15D1XvtWwR202j0X+cMPQZczoRqQxUDvXW1TU0t1fidqngJrac2UyqAYGtIb2JppS+c5ahejEWobeIuhhMULbYgXJfs+rTYjqI3znqtrRNN1FDk0tfZLtcdENxliKVA78RLGea1nSftPQe2WFyW1EZt9Q1wbA021ZnxaVUy62bi5tmtpcZKqcEepbImq26Elgo6Mc25nsp4Z9+hYgBlyUakydWGVNQqmPauzSYMQ0SB43lhWXMzWGvdvbndE4fIfj8RB1OrffFijw9CSitrG2iCH8F7VBxZlTlnPnt95vGYmqwbPJ1TGxj5fttXLzhZtEW41nK4LAvLPLMutYVTTXaodq61NS94b62xcTBmXMvgbWW+3m/XNGueB66Bp0Z1tY4J7A6rF6/u9FkT2nU5ip4Ly+V2g26ylzy2q8PQ2W3XyeNVOH/h19tnlJRYz2dyWukklFIqOSUrEalCiRA8ntBq7rUJMQque7DKpeW1se7o6caPZQxevLRFANLy/uadKNvft5AevZQet6jFdtmz7u2c949q10l7FaJfvy0kVxS35ae5bpnQ9TrZooyGjzRFW3FCwEDZfjlVK0X9dqWEDsxZpFQrbU6dLURajWKrNEqut3McglWOtJ9SkTZOyqO5MRZVKTVTqgF6XozVVkphzWkb2eycIwwJFUdMJpeNCIOze9t67ROC6Q6IGAhX1JGLMK+V85y3qu6ar1K+99i+Ym48lBXThUuJ8+m8cahNZcRQ5dK+gBNjeXl3fZNaqJVzZp5NP/s8B0JwvKx33N4PBPpklU5LbMKBDSjSBtZZvt7cuvS2o/ZZHQ3flA/bo+TGUNPGTe+DLy4UVlTJaaYkUyjdooByoaLW2ps1zTM9vn3kB7/7e6zL2ggpppq7tJX+5f0du93Ebjdyd3drggghNB1zD4NZQ17bDLPmqSsXGScjGtlZjK1nvHvTFkHT2Xs9RM+lNyXVRjUwXTrQJq/U8v9e3mq6bTZD3EpquVRy6TIr5vVMCqp9aNPjSqkJTLQ1MpfKj75YOZz68dvNnUsfhNFwktbRaG3M1v/gxDTgLMVxrStQrMegKqdj4nRc2mJvGHkMxZpmYqDS7jsfbXhkKaxrm0A0DeBC05+3aDQVR65iLdMNeLOOykBOhfNqQNvj+QScCeHIMDzinGMYTWyjNj0G7x23dzcMcWBOK+d54bxmHp4yx7ON5spaOC/r39mevSZY58TpfGI+ny2noeJctYaYzfO1ssg1+aY9B5BL5un0hJZi5AMHPiilvkK19f/CxbBEbJZpZ8o5SwF6YaWhJ89zQK2meHotjVQymlfr+V4WYz2tK3lN9vqmSrouZ9blfEXswMQRSlPX7Uw1sfDzzRdv+b3f+R7zeTGQq9rMu9PphHPChx++4vZmz+3dLR99mIkxcrffMQ6RGuvWS23GXnHObnJUWUttnVF2TrxcdZcpaJeIRrZFkuYJS7bFw3c+ktL6GmyB6N2DXdpLq6HYlibYG3K2UHlLkUQM3MvaiItde102Q7drrHz6euFHXyyUagInpgvXGHpdTUeE2FHs3cTtfkcIntv9ZG3NAVOKUUEaIenhceHt6xMCl4GS0R7DoPg4EIPYCLLRIzmzZit3hjHaFNZcwVk93qcmYOEc2YOJaBowWRTOq33f4+nMupYe/Nn1aCU2m09o3ZqvXinjNLLmxJJW1lR5OmbmtZJKZi2JJSejTL/n9tUae62cz6YB//T0yPk0451nHEZbBWpuVA9/BdAYZdM1TxQaaaOkhMPaAi21ls3LWVurb+/xltc5t4lK9hZK7VaIPotu29HSg0v7c4sUcqYsCzVnltORkjNpMWM3bSUzhHU5s66z5dZtv7VUaq6bIdfm2QTHw8OR0zGzLHUDMde1Ms92McdxRauNNo7hRIyBkgpjNK7BebShf64xw4J3SPQWEudinPSr3p7OYOuyUGjd6s+2QDlca7yQzdu3BXBTm22hP1dhNtCFLC8y0j29onllISVbBPoJUoVlzVZWKtZLPq+F4ylznksb8GALZGrzAswTXoQinJjB5WzDInIqRO8N4wnGbvNqq8nxsHI+23tzW8hCguBhHBUfIjFWhsETQ9OYDxHn6gWf0Nro0QpODa5ppC4Va/LC04ZvKuJrqxgYH6Copaq+69GJoyLk6pjXSlEbbLFmJRU1rf3i0OqQ6pHawab3275SY0+58KNPX/ODH3yfTz/9lBAC9ze33Ix7juHM6XTGycAQb0EdT48HjsfTxmwyUf4d+92Iq4WTtxsxNqbRbors9yP7/cQ0mUCFb0w68R43DKbf5hs/XtwGYG+ldYE+daN3cwF0CaR0PjI/viEtCw9vXpOWlXVebESPWh8UwLrMrGlpCLeZxLrmJpiZOZ7OLVw3/OJ8KnzxhbVndsNZlsrhYIDd+fTEMMzs92fePiRC8OynyBCNXjkMxq9+9eqe3W5kmuw7l6KcTivLshgNM3qq9+RovdFWJrN0o5epjBwSqE5sLp9YtaC0kL7kbGmCXAy9FsuGTePOTpsNOlBKsegpZyEtxfjlbVhCrZlUZuOeL6U1lyQejyvzWvnep4nHo01yWRueUZu+3fNGGwPeovcMwXgXu8H026NvgK7A4A2RWM6O5dxyf7FZbuIswhzGyMtTIQ6B+/sbbm4nfAiMu8EWzLRYCucqLleqa6IfteKCTX11OPzg8LXYVNo8olmRZbboEKW42sg8AyE0ngCWwr15zEBqWvatUWcxMJrqkBqQOiC/agbdr2rTqsznhfNp5ng8sZsm/L1niAPrkgg+4L3pyYPjFFqv9RUby12xtLpD9i3c983z+zah9TJ/3cLWn6gDf2Xo/blLnt5+b0BULZm8rqRlYT2fWZeFdV5Jsym7bMa+LqzrwsZY0zahNmXWNXM4nFqJ0TTY5hmWRWh21PahrC3X8y5TWmgc4mzdTzkxRE8IQhwcwxCYdtOmPpNLpJTehWZezDuHSPO6evlpedMF0HQtBRDncFqppQNfHXeol36EHiWocmH6tXS4KlYKNVAsZ8vpc26PUllT2UpLKSnnOXM4ZpZUWZbCupqnX1KbE9BnzWk39trktpTiCjm1aTfZyFjBO6IPOIGxaduVNZCz9eIrHZOoIIWiwjAnYlXilPEbp8O39grX9OIsE5QOdPZ0z1l52O43e37jGIhHRdujpZUSQALSZ+eptoakekGLlNbR15uBpBn636GefV0T3//ep8xz4ma6ZbfbcX/7gmGIODzeRZwEQpjQKgxtmISgzMsZnwTRxDoHlvOJNJ9BK9P9xN3Nnrv9nv00MY0DwXeeoQE7AFKsXioUcMVy0NavWbRCXm1heUa7bSezGJNvPR95ev05aV04Pz0aWypXpIFg59WYZKezEYQsZO96bt1jJx4ejuRSiWHE+8iyKMejDRNIa7axR9UYapYow+ozy7xyOh6NP307MY6BYfDsWvtjXheGIbDfT9zd7Y2D7syAjTue0VxZQ2iGYtp0Fk4ad2Cbbd9+F1WK5KZ004Cy2kUwhFwq87LipKB4VB1rNiM1QQmbwLKkwuFkAOR5KaRUWVPmeLbc87QoKSlrFk7JkxIsSxuZ1FIg7cbZxSa73JdI6yHvir+GtKNW8ZBqFYkGE7KfIve3E6UWzvOpgYoWNaS88vBUEOc4zmfiGzufn3z8kmHwDL42gDOYF/eG/OMqFW8t3BWW88r5lFmysGYxzQa0yWPJNqteHRQxslMI0SLKJFftwnauY4iAs3Qmp+YI39/+vlJjzynzox9+wW43MI179rs9Nzc35snVJo1YXXWgVjZZKdVi9UcULSspePJyJi+LKXh4z+1u4mYa2Y0DwzDgG8KrtCGSYGQaKSAFqa1mHIBOxih2Are6vMPG6ao2Ik4mzSeOj2/Jy8pyeKLkjGvzujRnltNMzoXDceZ4mkm5cDrNlFKt8UcC87zy+s2BUiq7HYyTY10q59NKzpXzeWZZjJnWp63WXBsxrEBNeC+s897O5RTJacR7YT4d8Q72NxPHwy3DEHjx4o5xHKz2XEG9ktbUPKQJLRmZxG/diL6pwGbvO1q6IfS19CEWzeAwwRG3SWEHcrIwvZTWpFKFdSmcjgspFU5zZk02S/3xMJNL5Ty3tlRGsuwpBdalUlLreS+d095y/VbHR6yxpM9Noxt7pzzUS3SYTeadu9vA/YsdOSeKzqRkKYSWSiqV+bigKA9HQ/vv728Yp5HdbuBu54hD61iLEe/s+FQqqbgtHVnWlWXJrEVIuWnUY4cnzuEbE7JX/513+CGwqR2V0nTtGwgZgk20UVPkcVvE+37bVz8kQvyG2GrR1q8sxr8uualz2CpbsiHc9PATmsJpB6HMGMZhYD9NjC1H8961UNaaYJ6VdrmqAW/H1G6QXtffirVgQ1cK6XykppXldLJ6eBN5sP5tC217yUyhTZ+ZiLmA2mxukYBgZb+7LG0BGBoi38qNTri93XN/a/kkAKrUmhogpZTUgDi1Wfc1Q80OqULFIV4oayYvq0Ujk9VuO2kE6cAcTbK4t1v6bdz1M6/RM5/Oitsqkw3EVFtENw8Lm6GXYlNVUiksSyb1kHxOzIsJMq6riUisa2XNiko18UkVfIgMGohEKoMdju8goppefL+0YmCub9cxtJKgx5sjqcbnB3j5cuTDDyM5wzBOpBxYUyRlQ/rP69p64g0wrEVZ5hVRZZJIEesodA2jEJpeyVZMtcvXR2DnUsgFi3hyNURQDOA0zVPr8HO5OSaxVMFXMXiJlgZQCR4YHKX1SLzv9tVKSYsjuhGqkpdMGayLyKuh3GlZyMkQ6NwIN0rGiyMOg6HuWoCCF8ENgSF4Xt7f8NGrl9zd3TIOBnYMw0AYBwqQt2kbbkPi+w28ySs5ZzPAVbHE2eqvVTMprTy8/px1nnnz2ac8vnltNeaG1K/zyrqkllvZJd/vd9yFgVLMe1nI7FE18sT9vYVnh8PC+ZxaeX/Fe+HXvvUxH7x6Qc6ZdV0ouXA6PBrotwin02ILXl5NS41Mdkb7dcWjXlircqo2NdWrI40j+5uR8W6HiJLzSq7CMAbC0AlLfSCha7molTq0Wv7pfEMkxEp0uVRIFlKntBrgqQVVR6mmqFqqDT08z4k1VQ5HQ9zfvp1NfagoS6rkavLNa1JrWvIFcYFpvGG3j6111nLmEF0rVbXOMddr6rb4hyYB5YXNkZgMs0WIaOW73xn47ndGai2c50jOlSUpa1LmOfP6zZFlzbx+c+bxaaEm5e0XTwzBE1/dMJRpU4l1eLz2SpI0aSxtxRnDIZZFSVk5nlbmtdB5HeKcKdUEC/9LNbWjMYwE500Hvw2WqHlBdWUYhX2IuCUQDg7S+9nfVzwkQgg+ABZLbe2ULTzs6qc5p+YVes1YtofUYlGcA2m68EMI2wnrCiDPRfhpYMilTq/tf90b2fHZpq0hxVo4V8q6sJzPLOcT6zwbhVVpYW8Ds5o36WKJcYiEOLR8q8tjG43UhqJYRLAsxnX2vlp5SITdNHJ7syPlRPBiKHgeEAqihZyCgXZeNkEc2RQcBcQaLEo2jbOSC9llaols/DPd/semYtNC+A2nuPIaHWjczhH9umHlJC5e3rIea/OsxXogrFOrhfUFk2nO5u1KY8vV3tnXLomjKQMF6wALrbc+xub1vGxS4UO0FCQ4iN6OM3TgtbbrWQtrULQW9vvAfm/8eN86MccE6woxOOY54ZwwDokQLGQuqZDqZf5b8O7SWNMiVDtPrqUXl2qF4RYW7ufS0hB1OFVK9da3T1MCUiV6NlakzdjrsHEr13lpVZNIcANVi2kT/pTtKzX2GCPf+sY3LCStmRgdeZ05FytlBH/hbNdamM9HDocT025inEy+KrhgkkrqGSbPEAM3t3v2+z3jaEqfqlg4JorEiB9H8+it3FaBkhLiKn7cIc5RUyKvJ1DFteELp8Mjh6e3zPOZT7//Pc6nI3U1XbcYBz784AOGYbTQuijgtoknuaTWCKFbjrs0SrBJISVKroiMTGNrrf3mRziEaTeCh+gCITq0Vva7aMqp68x8vm9MPYtAtuYYLnV2J9V06Eql5IXiteWRFR88YxzxIeCjUZC9c21aj9v20RfCS2PLtRjkpZYOxqE3Y7fcOZfCkixVWFMlJUhJW31dQQPipjbIweEUJoVQoGgga+t7aA5hzdW6zzqO4WxW2zi0Y94HI8GMjjE4vINpULyjKb9UUGc9AxRubgulnhCB3c6+UymeUgLzEnHOt060Hbc3ibQmjk9HNCcOD0+U05FpHLi/v8V5O04RAzYnP+KzMsSV4AuCafuVXFuPQDu5tbSmnYIkxbtADB6oPB2OoEpw3qoAQGgCF50KPoYbfv2jP8la/iifP/42nz3+1hUp6svbV2rswXs+fPUBuazkbFNKcloa6ytvTfw0T78uM6fjwVZJvTeSm3MEcUQHOx8Yo+XG4zRsAwgMwCgU0UafjE2eyqM4wwRyRlpPBtLG6p7N2IM3fOB8PPD2iy84n4589sMfcjoemGK0+m0I3N+/ZL/fI2I3Zge5BDieHjmfnxopyFb303llnq30BpWcBZGBIXpiGNlNd4g45nUhpWz0z8bR9jI1L72S5r01pmRTqiklWVulmtcyqWvDQESUUq35KGcl5YpKZHQDLkjT5wutdOlNkroXfK48eY+Y6oWMsN10W+27kW7AJqOmtXnyZvQ508ptYOOjLbWzxdt46b4IqTpK6gIiJjtaSiWt5vZdizJyVLRYTjvFvmi41igFu0mJQZlGM2iRgiMiOKomqs545xjH0dI4DWiNjKPRqFNSnExMg5VK58ORVDLn48qqlbTfMcSJEEHb6G/vAs5NiFNCGHBuRaRuAzp6CdNuPCu1ZbVI1/tqI/uqMs9nSi5MIbIfBrwXdmObCtvApBgmvvnyjwGVlM989vQ3r5hNP8b+ftUG/dO2UgoPb97Yia6JEBy3e+sd3sbaYlTSnNOmQqtY7hnjQHRqoZqDMcIYA847K2mIAVziHfUauOhAUruJRQ3EUVXW0wmWhfV44vz0ZF67yVutpxNSDR+42U0EwVKGEJgmI1o4F6wls5g3rI2Ek1u5yVpNrfQ2L5l5Saxr4Twb8r6u2vjNGZdWQHj7dOB4PtvUkNFC17GP/60ZdRVxyhCsdFOLEVbsHNqs+q5R7r1nGJ1RQUfPMEZCjMTBHps3d46LIm7brmm110jQhXaw1YFrY9R1JDmXCxpvqHgnMhiF1vtIHIJ1x1XXFGbalNUqRGd5/3lN5Hm1hWpt7b7YwjoHzzybDuEyL8Tg2E2em71puN3feYZBuLlx3BWbAzfEinPKWoS1mJAjvjPsMHkvlOAKeOV2L0Q3MMUK+QVpTeR5oayJEALzuuByoi69S3JFQ6FUIbrK3d6aYs6z8QlSSVTNxmwsPdTv2gOuaQYIwQ84qcbpb+e+j6HatPm3NPQy/OOnbe+jVDMB/yYwttf/r1X1nxeR3wT+MvAh8O8C/4Sqrj95T7AsC7/z238TJ0ZguL/b8eH9t9hNI1ApOSGqrPPMPBvra11XtCrTtGO3nwhOCaJMwXE/BcvVYiBrIaK4EHChIc7QYeNGSrB2TZFAEG8A2ePnLEvieHji8c1bAIZ28zuxyZmTEz559YEZUctrhzgwDDucH0hrYV4yGy6stHC116CtR/90XDmfV5Y18fhwIpeCVme5myssyfK63/3+j/jszQO7aeDl/Y4YHHc3I7sxErwyRiU4Yb8fGaOVJq05p5JSE/xwF+wiNPWVm7uBu/s9IUammz0hDoRm9IY3XJctjLQh3uNVya6LM8nGF9BuHirkZHr2Nv7KuPDnubQcPdit0xZCQRmGER+tHLVmo4+66gyBV4dXx5IKP/zhF7x9OpKT8RVQCGIMtT466SKHZRz4cbDmko8/3rPbBV59MPHRBxPDAC/uLZt7WjyHZWQaHcVHpuiYgjL6DFIZw8rglPvdjuBHUpr49id3pFT54otHHh6OzOeVh7eHjShUlQtT03n20x23H+643Q0ENzCvBdUDHpizcixN8sum0KGtu82JMEx7i3RrRWqbQ5MXVPImkyUOigOwvoGfEsG/n7EDC/APq+qhadH9WyLyfwL+68B/X1X/soj8T4B/Gvgf/7QdWYPIjG9zrEqOF0GK7k+6d9gUVFtbqPRQ0uqezhuw0mvDrS63seWk1z6wsAjXPPtV6Q7VxoSbWee5zTdTGxbQQB8frFnGT7JxwUUghGHLX0s173wd1qbVSCM5m6pILoXTnAyVXhKneW2cdLt0zlV8hlwrp2XlPNuxjKOjVM80ehvo1xmAHY0OjQegTdJZPLWwAYfipIkiGK02hGDevMlr90YjAzLfqdt2nre7aPwZScdaS+1NegWywkZ7qdrorBcG2GW3XX/Q0H3npKU7XXREcGrlyFIKa8pm7Mm4ESZYaZ1tRZ57tDU51iQMyTPuA2uphNExTp6xCHF0DAqnVTksplg9L7YAeZRAa6/G7pEYhCEaBqDqjc57GpjndRsxbaCyGbyr1UBTH4jUNnrKorBabYjjpjJ+dba309O6+QwwNT6/yYc35qDWLXqitoBpC7V++vY+SjUKHNo/Y3so8A8Df749/5eA/w4/w9gFK50FZ/pboY/AVaWkxHI+baqmwV8MuWplPltTiewj3gfUO5NnCQ43ROI0EUcrtznvcQ6CWHPBmrPd7EPEhWh547qyLCuvv3jN4ekJ7zy7yXK3KUaCd+z2O3a3+21hUBq5pnHalwWWZeV0zpzn3Ag0KykXjqeTdTilxOPxaHz445nTaSGlxOFwNi619FFHl4mpa8GGGayKPp6JoavxdumsRvqRa160rfTTNCINqxiGeFUfh93uht20x4fIOE74GG3BDEZAkksyCYCTwLjfQ1WbsjMMpJQQ58gpcz4ZSxDpHWi00cVWaWjrb6OyWghu2m+NQCVWSiuqjSNgpKpSmp58KWTxFN+qCK7VpV205pHGUEWl9b0LWQwAm1d4+vSMeOXu4cz950d2O8+3vrljN3kejytPp5XdIJweI7vB8eFd5OVNIDphH0YbIVVdk+q6CEC+eDERo+fpaWBZC8uSrIw4J9QZ6UelUGom5ZVaupruBZnv4boBg5VKbv/OpqcYsKabktCyGmHJZ6TNi6+tP967iMiVw/spNv++6rIeC9X/KPA/Av594K2q5vaS38MGR/yMzWrTvR7abR1oSPPaNOeat+8kDlXWdcV5W6G11dO06TG5GPAx4IeIi6YW4hr5I6vauFzV1trpgUzKmXVdOTw98fD2gdubG/Yv7gnesxtHYvDsb2+5fXl/KUWhkAqaMsuSOZ2OlofPmflcWNbEm7cnlpR5+3jk8XBiXlfePD6RkoE8p9NMSpnTeabW2vJl32aUGZd+f3vPOO3RZKy+GBzz3cRuqgy1VXOvRyS1YxPprEObWT9N47O/jePIGG1U9TAM+AZcSqcW94GFbc/iHL5Nv7GuQk9YgwlNBpOKlsX2r2oNLrWwzVATupZ/3fbrxKFt8gtiOapzrZKAdXSBlahKMUmmKh7t0gO4xkR0F6EOBS0XPbuixsE/nE7kWtidFnZPnpt9pHhhv488HWaeDjP7QXApsB8dpD2+OqbomW5jE4S0HJlGb1UP+72JmgLsb06Ic5yXBC41wNdAylrbZBx1iARcU+3pohzQskytppnSTpKqo1abYYdmqMn0+31G5DIvwLTvo/H034Nd817GrrYs/0kReQn874A//j7vA7geEvFyGolBWlnIbuS8riRnpJpOxczZdL9sQCAX8ZdaOZ3PpLRQdwP7KE17zeqxqlz6xGPYDEKcci0hXVTJtaAi3L18QRxHdvsdt7d3eCcMzgbtxV7Ka2y+Wqupk6TC6bzyxZtHTqeV4ylxPCXmJfHF6yeWNXM8z5xmy8/fPB1JqTRwzkpg82r3qa/tO+BBJnDO6KJ1AKd4iSiOnAeWNSDq8JIbicSDhsY1iHbM3qS4vHgTQhTAClibVryo2JBIKU1vs5XWWiWhg28N/aHX4jspyXmHa0oql/ZVSydqdeRs4FrKrrXYYlrttUk7XenCFVprp4gNU6jCnCrH2TTWivZxW13/3RaRzY2pNeCk3k6L2ECZWklFyCpIEnRRKoUfvT4xHT3n08r5tLJEYaqR0+AZiEQZ2I/C6CFFYQgQQ1POc6kdtaWVPii7nWkhntdIqtnasKORZWijmXoBo+M5bUWwhc8uz8YUtWhI200vCEaTdtJGOfdxzlI3p+l6FetnbD8XGq+qb0XkXwf+FPBSRELz7t8BvvcT3rMNifj1l/e6mzw5L+S0kldhPh/RkkjLgjYjX5fVeptTsVJFsSF7KVeOpydynnl1f8vt6BuLTRtZB5YWAQzebeGpiRsabbagJC3MxUpv3/zurxF8IIwjcbczmad1gVI2AFpL5Xw4mzZetWEEj48nfvt3f8jbhyOPTzNPTwuneeWHnz+wtFlfVZU1FR4Oq/VxS0DFNzINVBWj/Db8YRoN2Em6o+YBDULEarjzOuGOgZNkHh9mhuCgjNS7wO1+4P5mZ3rjvhjryl+k9WhSTA4L+QSHprLRXZ0lmTZMw5nQYu1ilHYGkFDwtaCh4kNodHkThDA43kGBnBzr6slFWLMzL9ty94qjqn2fWq2ds6inukhFOFdlWeFprnz+tJBKJavHhbE150RLp3KTxsawnSKwFGseKggFW9DPufWGK/isuNPK28MR5xRdCrpUxug43Y1Mg2c5eubTwN0eUGE3OvaTMg3W/hrCijSVfjzEqfLyg501/GgxAePGREQc8xrIxSo/GyplZX5M769lxGrUa9fuBSeKYOO2hYr3ihclBMW72gy9Nvn0/p5fgWcXkY+B1Ax9B/wjwH8X+NeBfwxD5P9J3ks33ogB6gT1lkf2gQfoRb5pU0blEp6UXHG+iyZYnnOeF5wIy2qkhyA217rvyBRlG2uuG+5VUiPOkOohDvhxtL73LucssomgdU08izy0iSsUlnVlXhZO55nD6cx5Xjkez8xrz26ElK3kkou2lkgbfVxanlldQ+PVNYjIm1BCtQaOqg3tzpA8xriiotV6wtelkgcDj6yZSBop5iL53DGBjbFIcy4N6NHNpTj6VIJNHa67+Q4M9nO5eat2XrfWVmk6gpY723OuAUx9r21kp+om4lC0LejVBjKmXEnV9Og29t41+7Ftm2SgcOHs81yCrzYDq1WZa0GkICtIMrbaPBe0wOlcOJ0L3jnOsyH/fbK3V5NO6403ikEmIVh0EwfPMFgKGWPYOAOlvnOi6Cq5nZF4+dvzmUqttiMt9W2Xxrd+/G1uXy8n/2Sz27b38ezfAv6SdO1b+JdV9f8oIn8V+Msi8i8A/09skMRP3cQJ+51DZELEJIOCKFIbgSREQhN91ALRR6ZJEPU8vj4QY+CDT15x9+KO+fzEX/3//S7ewTyvPL555IMPX/GHfuM7xNCGL7qIQxlUN+NVMt7Bbj+0chNULW2OV4tdjc9KqWtLJ4qVoIaB9bwwLyvzurDklSWvvD088sPPX7OshbfHhZSV3qNcVKh+AAcujjgf0VygmAfVEMF7qnOsJZiAYskIhew9mg2w0VxYosNLZZDC6iufc+T8uLB8cMsYIuMQiPdG0hEpVJKZV6tOVCck7UMurOfftPQb4ahNz+lafb1sSZfbksX65GqxUVVqmvCVNpmmEWdSsqilqkfVqiMdFZCGtpcEqUAqhVMTX3w4KqdFOZ4XDmeTe6p2R6NZrQ1Z2SSwUy2kYgMTXTQjc83KpSpOrfS3GVUVltX+PvrIFAdAeToVTpIJfiatws3esy4ru8nzrU/2fPzhRAwgQfCtGUVQnBfGyViOL/Ke0ABRK0eyLWCuzxXoQGI1W/DOI2pkM/tGrfOyofHeOwLVHh5ubwaGIM3r57ZQZOu+3uCzX8LYVfX/jQ1zfPf53wL+gZ/5CVebw+qgF3TZN8acCUKGJuPbtARwzuroqsp8nEkh8M1v73j58iM+XVa+98PPqSXzYr8nKMY2q2pKo21YgAGCthJnNY/oBIbYhSZbWaNLQGPAEa2ilZtMsjiPzd9eWHNizYlcMrlkTsuJt4cH1qScFmOLNYVLVBwqJmQpoU2joYBrn+ciuLDlrOZN7W+11A1Y9FqpyRFEUQ/FKU8spDkRQ+T8IkMzMHFtZrfmbXil6eALWRWntKkyJlWsLRe3UVgN7XcWMkvr7Ovdgz101kbi6EIifV2oRVvNuen3cwW00rxXpSmuNhpswzHOS+U0V85LYl5NE90H48EbAGjAl91/huGkUgw8CwbaaVV8VaPvrleBSNOiz6ulKMPo8XFAa2GZTavgwa9Q4Tx7gitG0LkJ3N2NKEbnNbTAymBOHCEKzgu7/YALYZPiKkXxoeK8NoDXHtqqZNIwCLBrUaSJcWhpC2S1fLyB2iEI0xAYh0vqZJ2hTcDjV0Gq+VVu4iAO1uUzNmprFz1MrrLqyhAq97cj0xh5e1jIZ2OV0dRLjXWWAcft7T3UzG63M3Q5BLqMNLkgvphlh82vANpCPAPtQmzDJZ2HLs1bLA4VBS+egoXsOWWOxxNPT0cen468efvE67dPHI4zy1qaumjEOUduAwNUTexRRRgFBpFtdrxiNFNav31tK/puZ3LZ0TvGYIrwrhZyUyhM1VLks9jkld1h4e3DkWUduLmJbepIMbVeaaVwNe61DxHnLSa08L0tbiJNWcW8PC60oRpsC9f26JtenP8Wuvd/q/WxN8V0EAPncgvb11xYVmVeK8dTJhU4z5azp1Jaec4CflFlGAam3QQIazJFV+cdLoQWyNr3cbXiqkUc0xQo1SS2YggGIN6MoMoUA1MI5JQ4lETJkKpyXo1U83CoLMnxeNzz4pwpqux2BnN6V+lDREwOS/BBiSrWqpsu5CHBGJv0VFCbYbpLQumcTW+t1dI3J00aLHi8KBG1KeO+g7lt8RKl5mqI/U+rubXtKzV254TdznOzG9mPExdRwkpaMgszu+j55kc3pGxe9XSYUWe5LATWVDmeFhTPhx9+ghfl/v4l037PEAfA0HNSOwHDgIyDhVftTuwzycRHpnFHnPawJGNXdGNXxVWILqJZbWrNPPP6zQNffPGG128PfO/7P+KLN0+8eTpzONnsrzBNeAms58S8rJuKi6pyo5Uq5v2q2sUuxSSZOjcieM/+9o6XL2+JzjOGAFU5vHlkPpnUcqm24uelENoAAxFlvx/Y3UTEO8JQGHdlM3Sn4N1E7E1BzuidKi0ZdDamyAw9gh/sXHSk3YUW3l/om8qlUtLoB1cPZS3FPHztxg4ZIyGdl5XTbCIWbx8WUlEOi2POjoqVI82EV0QzN9OOjz5+gSo8PJ2Y12wGLuZNT6uda9/CZK9KHAbzyMPENE423slbBOAl47hwBYouzKVQzoVzskhjHBx39xO7/cjdjeN230aFBZtRbyOxLHyO0cJ5q7Z0mXC2SM3C97IJdTaNL0DaeCwoAhnFe4jRMY4ej42Ijl6Iga333YlYv8OaETUw72fZ+1cuXhGCa+UCNsaZsZXaCZTL790ARHvHlbT+4EwttTVu0Eg0F9XYKzRu2/q8da46uDYtuws0aBej9Vx2dpTNNDOhyLRaI8u6Jpb2yLl5r5ajIe1iOwvVdn4EMXrrtBvMK0kjVqh5i84c7Aq5ffpL8AGqdapZk42JflSa8I5aTTmlQkqFdc0sawKvDLzDsxA2kK3PpX8+zOEaCJPLe/QCcD47tR3su/rZ7+H+8/rvlp01Ke2iV/p4ZZOuqp28JBbqxmDNJePgGaN57y6mKT7i/EjKmfOb1ToNqz6bXNOH23hvYidjjHjnrflGPLVUQvSk5BrS3sQdS8VlZVmtZDq011hZs0+abfeMGpC23UMd1NyQUNmYb9vJ4PJ6Lpel1c5lA966crJzsr2m04TBmra0Nqrzs4v9Y2zvJ//pV79577i9HQkCYCo0pU3/dChDDCxL5XQ82gq5JNDeOmhkkNNpYa1vMJ35BnKEiIsDhIgGjwZvdfboUecaOQFEvAkatG5XnMfVCslKbf2irPOZkjJpTTbQYk28ff3IPC88Ppw4HBYOh4Wnp4XDYaVUxzjsWXPh4e0DuSrDNLHbT9y/uOcP/+HfYLffoS3jW5bM08NsRppNm70Um/4pIty/uGF/M5loh/MtpbjnZrdjOS2c3hytiwpADOhaMsha+OLNA0s68f9n7t9ibeu2/D7o13rvY4w557rtvb/LOafOqSpX2cQoiWTLccQdGSKQgCgRAkUgHrg98BRFQojEPPCAhGTe8BtISChIgLhIliweLENQXpAwiU0AJXbFdlW5qs7tO99l77XWnHNceu+Nh9b6GGPts89X36lyzqnxaX5r7bXmmnOOMXrrrbV/+7d/e/PRiePtrdOH1cJGsfMTTE4ppIgkK+KuNNg96o6/wf5rc0ht3VZD3at7dBOQ1D3fZf2a1TTsS1XmxTbKeS7MpTjd2KjDIiY80XWB73zyymaV9x2Hk6n8fPTJGyQNnG5fcf/6Y7786i1/4//2b/CDH33fspBgQz4f7m+MJRgUCZkYe25vj/Rd4jAcOQyJp8cL754uhBRd9ceIK0ut6KJ8+faJIAuv7ztO3R2nY+T+NnBzbAQPC9ltMkybUdg8uHg1QMkZH3Vd3Sbt4omwYkqyVlGK6SjkSt8Hhj6aRw+2XaYUOAwWeR37jlIK378Mf5it/4LDeBEOfXSEt4AW620v3mkUIxOVZZqZJhv7i4sCxGhh5DIvTHmmGyKnlJzoEV+EobrVKWia5OAluBBcWNGsPqgie0lXVfPi08Q0TozXkXm26TXjONtjMkmlyR/iopFSlOt1ZM6Z2Hec+sj9ww2/+ad/jYeHeysRLoXrdebLgxFtpskUZ/OyMF6NF3A4GkMrirXzohCPgnY9FLhwcSMyQK94GG08hJGqM6fbtOXjwRJBXcs+BnzFLllQIawefvPq+6XzsnS0ZqNtoGYr4amuRu9qcb7BtEWPa9IZl7xRYku1LjEDrnR9mxQD93cnPn59XHHTmCKn1w/0x1tevfmUj7/9PU4/+jGqhcend94vIAxDx4N2ruFnjbIhCH0PhyFwezNwczoCcDxZdLDMkAHUJ9NU5XyZSGEhcOB86UETh75j6GwTbToCyq7Ft4Xt7t23dHVXYlb7m3adt6Jk+5tiqD2JmBIp6LoZxGh9GwLQJWot9N0fbsq/WGOPgdu7E8s4kefJmjl8g1T1sUIqdN2AovRDpl8yKpF5XtBQoDfALVV1vnFYPZG1DRZijbtGA3m526lu3gts02FLOrUszOOV6ToyXkcu5yvTvPD07pnrOPPFl2/58edf8fhsYpKIsCyL9eQDr17dIyHya7/x63z3V7/HRx+/4T/0T/wmp9OJL796y+PjE6ebE/cPH1OK8tWX73h6OnM5X7heTV46l0ypBVxjLYjJR8WDILVSrotpt+cJrTb4cZpHahWuV1N3PZ87nh4PdH3kdIqkLjAMYh49Nj4+HtLvdOfWkJ6dm2gLcA062aPipmuu69gnS0Vba6xNSi1q8sjXcTJRzdFENeelCVgKrQnZwgUrLd3f9nz85oZxGrlczy7lfQaBL7+A5+vITz7/0husZFUL77uOb3/rEx4e7ih5Ji8zXTRxSCETpJKikZq6ZOo31IAWm/obNRHERi1NU2YcF66XhQDkGzP6rY62KfR4TE/rp1ivkSPmDQfViGEmGP5iBmI7WtyF7V2XOB0PNus9TEQxRzmNRh47eK+766t+7fELFq8IvHl9x/O7yrmMiCou3e3tmdbyeTicSJ1wmhfmurgE8UhR6LQnkqhd8Ly7gUZQsdlkMQeSX3Rj7uy8mhgxZd0GfNKqxaCVOs9cz09cny+cz1eeHi9Gg/3JOy7XiT/4wWf87h/8kDlX5sm43vNsdeHD6ci3v/tdbm5v+Yv/kX+WP/8X/jy3dzd851e/ReoSv/07v8P3/+D79MMNrx6+AxL53d/5A374w8/48vPP+eyzHzEvM8uyMOeOLmzjr443B479gUPX0WGNKNPzI8s0IUxcL1fmaADfsgSGg3K6EYZDB3LLkQ4QE2qIxodvkY40vCP4bPO9V1/zzv2Wade1CUtUNdKTlYHiir5LtNerOZum4Lzw9HRmyZnn88R1XMg1UEqk+lBHu0kmcR1E+PjNkV/97iu++OJzLudnahGm68CSF54+/5x3zwuPT882RCNtG9Xp0POnf/PX+M63P+Htl1/y5Rc/wWTRKuhMlEoXhT4ZEHaYo+mwV+O62UsppVw4Xyb6CE9PE5qVV3cnau0IZIgWFTbSFeoAWuv78FzHNA2slz4lN/a4YRqopx+hs+c48n4YOu7vbohiI75EF+Zp4nx5pE+Jm8MrUpdIsW0wX2N//1is+Jsea6XH0MS6cyLronKRA0HWVlbxJv+fktxxUGudDNIoni/yTllBubZA92iyOCCktdhop7LQGrZX3e6cGaeJ62iI/DTN5AoiadVY77rK4XDg4eGe+4cHXr9+xatXDxxOB1IXCVHoh57jzYm+PzIcD0YuqSYdfRlHxmlkWUzi2RpkfLN3b2Dz7MzLhwBlitY44h5pA4lanpiJuwGKTQdffCWuiPELQM6//5CBs7ue7+XwbeDEfvGyXluf3rK2ZzZQyj6TtbiKKwdv72pRX0bLDJqJoUIVSp4pGpiuC+fzyOVysUgHr/t7087Q9RyGAyml9dNHfz/VwrJM5DzTaKnGO7fXSMGo2FKMBmycCxtZZbPs7FMG9yltLW4ThFnPtY3g3i3yXby5AdTb5ZXd63n3oJfnAomSwzp7b2179SlGX3f8Qo3dhiiMVG38aoG1tU9QF2Qs2ZoYECGkRCTQFSWqEntryRSBPM8ECtP1wvUM+e5os+CiKcgglsfHrlsXsa4X0g3aB4dPlyvXp2dKNkLL0PdcZKTmwjiOfPbZT3j79onPv3rkfL4SYuJ0f0vseu5fR6pE3nz0EX/uL/wF3nz0Eb/xZ36TX/mVT8maeXx+R6mF090Nv3H3Z6glMM8dl8vEP/yd3+Vv/T//bc7Pz3z++WdEET75+DVvXt9Z1FEmb4LIwETfQXc/UEuil5l5xDq+sg1zPJ1sFJSIcB0nSwWCqfPG3oQ9JISVZhpbuN1q7Cswx7rxrpuvrPqpRshxKm8tjnPkauOJCLZRLguKOAkpU0smRgESh4MQY0eukBbTh1m0oxBXiupxEJ7f/pAfyudUrdweKkuBL54+5zoJb59mvng7cxknlusFzQtpOHAcDtwON5z6E6d0NKmry0xKidNNb9NRL088fv5jruPCdHlHzQsRl7eKgZuD6eOVuVJnJaXIPGWuwPViIX1y1RsJOA/Kc/NsM0XMUehOL7CALmhdbBenuCMygNocYUCkUkoTI7EUJGDRXd/B0FeWwcC6kieWxUZ9/2HW/osd/4SylExF3WMbQGEbmGBo0W7WOt7REyEmI3nE6NrmYOqvWcnLQl4Wb48Nm9qrtPpxorGHLdJpLZceetVCXmbG69WFC0x73hi2lbJkzs9nHh8fuVyuxsMfbG7acOgJ/YHYD3zyyUf82q9+j48+/phPP/2Yu/tbLuOFL56/YMkL9w9vuLl7YJoqb79aqMx8+dVb/tHv/T7zNPL89ETvQwKOhx4tYgi9KiKWa8YYiYdELYEyJcsdS0U9/Ou6QNeZumleMrmza9FGYkkL9/ae/P1I6KeOvcG/B+KpOH3BGH/V2X+mS2d1dhPe3JSCAVfSjUjxqADvESCQktB30CeYx2eeHytd33E4Hiy0nq9cz4XreeH6PJkSULaILIrQp54+dvShowsdoqYMGzHd/KFLnB9nnt59ZX0Ly+j5tN33PgnHIRGDsGDil1HE9fSKCZPMNh+uVhei2AG8hj/rJr5SnRLqQzFXiqjUtcy2GrtHTVorleIz9gqarMLQ95FATxSTKZ+nq6kxt5GwX3P8wuvsKtFOQm2gAW0qhrYmE1N5mbPyfF54d81kFWYFlcBxME59DN7dgNrwg2TD+9qAiBf93gbzrqhx6zMGNS61L9ZSK1oUsiGh0zTZaOlpNPZfl7g5ndBgveCn04HU95zubjne3vHm9T3DEOk6TJwjCUrm+fmRy3jlfJ3ovvyK8/PMD3/wyOPjmR/+8AemWluKda2lSJdgSJBrodQZQQ2ZDxaViBaXjp4RZlKndIeDc/5t7PDpJnH/0DEcOobB9OBNKMIFM8J76Lvujfx9NH67jJaCNjWhbUqr/VmbuWf5r2pw7ncAcQ5B11Gr0i3VNOPnQim2WJcyWRkPTNgyBm4PA6/vkm1STih5dXdi6GHoM6nLzEvl5nTLuBS61NP3hrQ/vf0Cysj1+ZFDF20T1IKWhZpHar4itXLslaqBLnZ0sSOFwKG32e7HOMAhkKTSxeIpQOMIWMbXzJUGyrkMWkC2Ork0OXQrsRHUW6+FNmC8KfyoqIt7CNcp8/lX7+iScHm2lts+KX1XSFG4ub0lCHzv/G3O4xO//dkf/Ezb+wV7dqGGSJVAwUQiJSQTGdRiCqRLZRwNlHv79pmfPF6sWWM4EGPk5vbAoe8sLMI1yaKpy/RdWskn1r2181TaPI/6bPAF1HuEndqZ24ghb6G8jBeenh+5XCcTfRx6Yh853SfTrD8cCCnx0UcPfPTJp9ze33Nz6ug66HpIvVA18/bdl7x7fLT+6gJfffnM3/+t7/P07szv/s5v8/z0aB6lt16AQxIOSZlyZq4jQiVJpIthy3lrAb2CjvT9wMPdiRiFw8HUVh9eHfno41tD429M740gFDUKawppReHRdplkB9DxIqRvBSbz2Bvz0YQqGj3UWzxXEU4hKGiIRH/tECx9mxeba/d8nZhmU/ehTNSltcMKkhIPt7d8680tS8lMy0yNgfD6hqw9D3eV+/tKKcKcI0XDjrqb+fInP+LzH2f6LnIz2FyBUAualbpcqfMTIoHb4WAg6KHnOBwACM5q7OORLt5Qy0wezwQ3yGWxtKkWcdyj9YkVC9ureu5vUlTJMZfgRi7Rp9mIcUPBaNBNU1488nm+zDyfnwlUUh0JFD56fcsnH99xezPw7W+95nTqqWRuU8eP337xM+3vF+7ZW1vjyq4y+ME3RJfcrUYyqbp5FnNArdzjQvkedu17eXdP++njhbMSfPymr3GnaAaoUlExElDXJbq+cjgMhicQKbixH83Yu860vrVm5ulK6iLTdLUQa7EJJEGg5MVHIE1osSmdMYjx4FPkdDpwOh44DB19JwRNhHoAVf9ZRDESjqgNM9AUPXSPXmNWT3si3WCfLbRoJzTiTEtz1poELUx/eSHbP9RxjvZP//fuyesQzILfVfNqFfPGun8OQnLUe+gih6EjxkDRQEyVlKDvheMhWbQWrFZfY6SqaeJlIjkLx1nIEUSCM/DaQAbIFLSaQKOND1PT0seGSRwPHSIuVxaSN5pY/Vrc2KP4ZBkVapD1atXGbVgsbDf/YteoefGmK9CorwochshxjlRXRPaOL8A2xoYf28AOgVpQL2ea6k1eh6cUTxNAGbqeu5tbU6P9Gccv1rOrjfrRrK5CI5hCi7DkwvU6Ms7V6q+5mgzV8YDERBgO1plFZV4mDn3k9uZE3yeXCFpjSTxm3x7+c2lddmt+6gMhtNL3PaebEyUXljBRlsLdwwPf0sA0LXTDLddp9gYXI6Qc724JKXGdRs7PXzLPzygT/WFgWp6YpifGeebUBcLpwPX5S87v3lHnysev7rg7HHn+8iN0mjidDnzy8WtuTgf+1Hc/4tPXR/p0w2n4FgLkySbR5GlhfJ4opXDsTuSlYxg6bk69VxlnkMLhGF1JNtINgZAC/aE39Z1g+m+Kwf0vp+XsKce+GD3XrLqh6ntkXQQfwBlsiGM2bkSKERVrb/UeuVaPoo/mCU+HjrubE1Vh8T7/lIz80id4uLEmoEOKnAYThVj0SNHEIWQSRlR6rFemavrrGqEGZThYeB6CEoLNO5+vVwBe3UV+5ePvEEIg9YNt9OZoDbPxUWCX5zPj5YqEgib7nRJYfFbfPNvoruMBuk58A+voE4hUhkEZBjgcOqa50vXC43nm+ZL58mmiqhDSEYkJWZSsioTA6TjYutYe0YFaZubzRM2mkLwsM/MMl8sZmG3c2N2v0//tJkX208cvOIw31ZLGn6yKc9bFS0XOqCrFxiyLkFKCaKIA4oT6UjIQ6bvOdOOdJ/whOPLlT8QAZ1M7s/zXRTKC55NBAnXOaFWGoefm5oauy4yz0k8LSzHppNglbh/uiV2ifJl5fH6k1szjI3Rjz+39iePtgaomfDl0CWphmUaoJm7ZxcTd7Yn7uyN3tzd88tErbk8HHm4P3AyR0/HAm4dbAvD0+I5pvDIJ6JKpGYJ2lE7o++SDDZTsbLXY+Ry3LhI7G/YYWorTWm+3LvNWhPsASLcrGa2lpF15DWjz3GO0MpKqo8wruC/eHswaTUUHUrsUGAaXqJaEhrAaexRl6C6ILiSx+61igxqrRkquTJ0p8lxDpkhup2MetgOj4CpNWz3nBUUZuhNvXp1MbKLvCRLIudi0XBFS7EAhzxemazHEPLb8fGMJ5sUELdowyejnBNCrGXxwxeNhUC6jdfTVqjw+FQqex0chVGm8Gosou2QREmLo/tWl1Vq5uRSWZWZZYDicuLs7/cnx7GDhVtOCA9Y6rf/W6pmlOJ3SVEuiyyEb88s8TimZcbyiNVFLQuhYFWkE81gOaNWcPTZKL3JSk3yeKSVT5sUGUlQl9T0pdeSixHEhAbd3NwyHwjgXrnNmGA68+egVw2Gg6yOHY2+LqWZUlMvzIz/5ofHRi7P7jinwnY/f2FCHJVGykv7Mr/MrH7+mS5GbY8fQRR5uEsdY6Jiok2FnkYU+QugD8dRb+HY7gEKI1imlWpnyTCkQU6WyoALd6UAaOmLsWKo3GqWmVIvbuOMcu95rCAY+xEooJ+skCx2HeSH1HctspNjpmlEf82S6/C45hZXeUDOM4JGDjXAqRjdVI1IZxaKgmGZ8qjbUEB+dldWqLSLBhj5K4iDw+iTkEjl0B5bS5sw1x6L+b5vEWmphnMxQ7k6Bm2Oj1po66zxm5snWQFmuaFGSXjmkTA26Dh5JwdpKxcuaITRpclyvsLDKiedKrjZayurzpsxkrbFWjRKpvjF6PV6r1f8pDH3kMAzkBaYYYGncf9vEzpezld7KTM6TA88fPr6xsbtSzb8NfF9V//k/ypCIlhc2YovCThvevLx1p3oH11KZi4V8IdqYIgm2O5S8MF4ztSRKOW6ReZAXj6omU40IoeVjHrJWVcZpYp4mtJhqbJDAcRiIIbLkQrpckRi47wa0Ck+XKzyPnG6OfOvbH3G6ueHu4YbXT/eM08hPvviMaZ54fvyCd199biOBhgMhRh4ePubT128MUBotsvn1b32MIORl4np+Qih8fFO5SQuimTJNiN+oLgk1BI7pgIgBhiklSp3JZaLUzPl6ZclC7CuFyUZa3x043JxYZmWZbGENXXCGm2fqjbUjVie3HUYgWv9300IP3QS1UJYJMH2C6TIjRZmnTJCFFDJLKYyL0WebZpSRXdRR+zZTfb/Zt9w1EbW3SomX88piZSijDs/EmDh2PXe3ByBSpLcW2mpAl6p9X1WZvOkml8Lz2YhS97fC/a1VTY5Hw2uuQbnqwrIsnC9nci4kLZw6o/OWaBtXCMUqIRJMcCXgkWL1EqSJns7eC1E0UKpt7qXk1eCtodUqFW3WvbEHlWWxVubDcMPpdCDP8OySYa3RBypPj0+IZMbxwPV6YFl+tmLNz+PZ/xXg7wL3/u//GT/nkAizRSN0GOvNZJ5LNqiiTRENXiMPTTTRVTgbC2nLKN/Ly/d5um7vKS/RJnuqP+qe0dX44Q3hExPqRxQcRT4cDiiB483JBk4eB7IWqihxjFynG7o5GeV1yUiIRmaJNn9slTXSihSc3x9NbipZuWboIkO//5R40msEDqqrve615pyJFWNA2TT3DRDbcmvTn3gfwZQtUl8vWoPrGlTvV1Is5dHadOzb5dIXD9lexh6qm26aNGQaF1FtyJSCsFNPbfyC7TW9TmpRQHH2ihODrE/dnIb6uep2QsQipnxbbNKr0VgzNc9oCNZnQCVotfskauE1BhBGCSvQaMujGae3sO7EYl6kOch67m1KT5PmtiYvA1BNeHRLSY34qOtzh6GHOpC6brv/fm5tvuGHUtl2fFPd+O8B/yXgfwr898XO9j/LzzskQgIpDSx1Zp4zecpcnq/k2doe++FAJtIfC5oKxyo2eSREL82pDe9z6dwo1h4oNgjbpIhseqCNA3VWmBnstsCtIlD9q2mbtSmmAi6rVJAo9MfezcjkjB8+ek0/nEhDz93Hr0lDx219MOnieeTTTx9Y5pnr9co0mfcTV4XJUyFPT5Q5szxebCJMtYWUYuTY2+yxN/cn3tz31GKz4VULy7xQs2uqBbNKzYWlBErN5DKjKIe+h9hzOh7p+4EUE7rMlFGR2NMfBmO/oa49btx4VXwSa0W6zlpfVa2lzrq8PRdXwwEkcQ3bIluWhWXOljLVgqgZHyJE1DcJV1wRSK6TQcV2dOdCiFg7qpWZlS5kohT3eVYmtFbUhZpn8nyxCkN07kAwvgVipTuCcOyFgqH1dzdHO29dqPPFPP/zO4te1Aw7aeWUBI0R7S0q0Z2mXq4mJFmrjSwDJRs6+qL3vAVLQQJBrMOw7yvDIByLcnNjZKJ4PCBdT4gC0Xgg8zJRa7aV10W61PPpp59Q8wMpFKLX/Pt4WIUwlyWvjuuPbOzA/xz4HwJ3/u+P+IZDIva68d95c+cKJPhUSxNbyIsJ6YcYibESYiJWMbKM2uTQoo2R1JJMf33wNMDHRRWrkTcJFcOHdgCUX4wWKaydVo2Hjy08rRZuhs5UW8UnmNzcnLi5e0XsE/3p4G2iluvmZaCTQplnLpeeqyO/+Gd8rhcLy8uMLhdDVotpo8WhJw039NHagI+HnpKFICbBpBmyWIdVxUqD6rPY1UNDCVbnjl1w4pFNZ6VWtGQkJvccQilsC0P9GlVwaRucpk4b77T32iEE1BmG7VpZpOZ6de7WxJ11gwGCe/Tm2beJsetV8lRMkVAIotYAIpUqm45dGyJZPKKSAFGjGZlTpUWC7/VWqqtio6VMCySQp4U823WbZ1MS6mOyVAVXMmusTscvKi6gmUGKkFEyLQ11zb01ktjiIYtWPFKNwQlXkS4lU+VJEYlGDOtLtFQk42vQUs4Yo0ud91BHtIy2maS4cv21bsM4PnR8Eynpfx74TFX/toj8pT/s+e8fe934f+pPfVtrcVpi6qhFiGlxTnxhWhZTCImRROCYevrQMeXC8zhSqzJRyCXQZxANlFJ5+3hZ4de7+x9wOB15+PRTjnd3kBISBrtp6uJt6pLUCLEb6F21JnjoGrtgtdm+o/NyT+gPSIz0/ZHOR/wKFcriC8IaJ/phoCYba9T3FllItE6w0+HEfDexTAuvbm+puawkkBQDfde59ruS5wu5LCyzDWrMuc17b0Zq6HqIQup9BHMQukMkpkB3NC8eUyD2A6GLSOhBveSm/mg5+rZGTXuuePdHMYKINRm18NI21kZOsvFObZW1wNIHF4jRj4OaMGOK7tmTfU8VpK6QqT1ChWDtoEmKa6Rbm5iqzXev6+cppmRkpR0TbGzc85wMmwnRvLRCVrt+tWxy31GjU1rlBTvQ1r9d6zaFxSjcib6JeLr4Y4rGcLROzLC7Hr55ursxTfgtvTGyl+nYldpAOx8MoaBUSl0IEjkeD6YTHw6kkNG6sEyPJnShL3kpHzq+iWf/TwD/goj8F4EDlrP/Vb7hkIgXh+J6a5GUerQEUlrQmik1c51m01eL1rLXHW+gPxKuV56uF6sz+z1akjUFdzHw5dsz4zizlOIjek/0w8Bp6FAGSC7x29rs6iYJ1fUDsdv04m08spE8qqcGEiPp5tbCW42AyyyXxVdPBJ8a0h8G0I6hD+jSGQh2OJhR3c3olG0QxvnqQE11JZ2mEFqp+ZllvpJzZp5sTFR2Ka4m6mgbZm9G03e2AUWhO3i+3kfSwck/w2CTbduovp3H0tVzNS+km5Grq7Q2sZEWB7X0x9OMshP/aOBnwD26ri/sG5kFQqanJibq2bpybDQKGirqYg1RihmKzzOzoMFVejyia4q1KhgnHdeo94hOY0SjiXnUlZiFn7NNjW0euzbZjXXvsrRJnS2oCqkPxC4Sil1HE/MMa/mNVmbUplrsmobacCteTHDJDuhtxm7vaVtwpZRMF4Xj6YbT0Nu8+UFY5itffD4xjQVqfoEZfOj4JlLSfxn4y3Yj5S8B/wNV/W+IyP+Jn3tIhA1lKHGh7XXrOKFkU0apQoeJDqqX0lIQUwdlA9RWMC8ErzsWn1u99Q5rc5vqWulBTDYZ3zVVDchR8z7izDzrDDNP32SWV+1zWa+LNSusjR+7r6qGG9RsAEterG+8tVJiaiOC8a9rUFc2qR6eVt+p/e6Jg4f+uRsLLqVI6lzJxOfUxzZvPUYjETWRSI8+VB1pVzPy9h+09b1Ld3bgJX692tetdXO7t/Le66E7WLQBde89wvq3G6Kqog7a7TeQhliz6heu5+EbjAgrDqM43ABma+3DyMvzFN84JWyfVx3TAVxPwNMADDsIjieE0EqePpBqzUqajt4OJX7/aJe11cz9PRsjTvy61FqY5xGhsCwDS7AmIpPpZm2xrjW/wKU+dPxx6uz/Kj/nkIgQI3cPr6zR5flMEUiDNTkcbwpFlVqEebGpKLNCLjNDFB7u78iuXZZzZkiB0xCNcyzVJ23WNUyilJcPxLpLuo5Qld7zmybqvFJKaaw6NXkrV3SRUmz6gcm0ompMPqMwtlG6dR2eIGrIruVbFk7GYsQJ400bSYPQmnMqWa07rGhmKlartc1J1vFWZhi2AQ3HG1LXE1NH15tnj53lf5KC8atDQKTH0pgOtF+drScDrCMcGlQuO0RDmyiDe10nc7SopOmVxxDRKMSQV5RYvL+9KVAHz9NNJtry8YAQveAh/qkUqPKyhCRSCcmjDSqhgHV4J0e3baxVKZXsVOt5KS6FBSDb1BjwzdwUjVLXedOKheDF8/iqSt/1dH3nCYOXxTRT6uKjuxyDaoo74Go9TrcNvOSV+LGKmVZlztkCxGCUXLCqSgCmaeTz6Zmh7+h0YToO5GUAPQCFfuhJXYCzqTF/eGex4+ed9fZvAv+mf//b/JxDIsyzmzJosRRrFaiIyfjdJQhKNB56gVqUKCYztHpjvxgpWqlFpK6eaM/w1mpGu9ZBrPbhwetODENMMit2LTzP5uUNUbH8LTv4tBqCe1+fjtLAqVJMSNNU0m34npbi5pRA2yz03XVxL9D+pimw+kUDxMtcnhN6tJH6juRjl9swwZBs03LZ3VVF1iBvb9Z44XBk/RSy0llZgbkmoLA5+C2n3SO/a+urvCx07kGqXUVzLdeZd3e6rj+3rvDpzgu3+yysIa5tU65YFBKNmKtabSKMv8ouSNha9NfXdDUgEWJIVgpFyJJBDStIMZlDEBtjVXPxuQOGtANoZl1RK+iLrmW67Ur5dW3PVeu2zLXaGUlgw6CFmjNLHtGamaYjKShDL+QcPbqILrcYaQrMP+v4hfezrxNWcFBuXijZ1UWxMlA/DFQNzJP3QatpmK0hmmKyRMtCCvDm/sjpeORwOND1HV3XrYup7bBrHipNLGP3uZStswFYYzrwNKAllU6Y8B3cqLyRUiKlGrKrS7XGBe8Gq1huK0AXbLjjmmOi9lq1UquNbK6qSGcCCw3UAQOArKzTmISB1A2GHsdETD04Gi2+qeFRAa0jSxKQ/DW9U+39uNp+6DG2IFLWkFo9VSrZVH1s/zTq8bbBuky0bqqyDRXwK0gTq2zAYNv8wvq917ZlM/jQGhmxWnVd33O/rTiW4Q0rXRJi3SndCp4ReytptX+Vmo3LlgZC6g3TcahimmZyKUanPiQDDZPJepmxVk8rq1UG1BeUegON2Ba+pjHrp5b1XFsnYRAhpI6qlWk0aWwb2Wzdnc+XM6XMKBkJ1uJ67D0yCom+P/zJMXbUQo1azQPXik1rnbOVGhAkJFJ3BAKXMqHLhKIUtakcLeyel4VxfCIF+PjhyM3pyPF4oO96y1/FZZP3qEUL59vUk/1HUzM88UW+oksO3LW9uJZMydas0B1s4EIpCzkboFc128yzoqt0cFtU2Pg394yAGrXSwmIzdgXS8YZ+OFiJyj1l11kkI8Gn04ogpLVOTur8vPaU4MaTbl8jQtw8G8rmUnf+2C1P6uatq27ltZozNReoPjGnkWIwY6+lUtnUcFoev8ZEql6mUvdi0vaW9aNp84jSjN3aQtFm9G4uyva5adzy4K/V8ndZP0vTpV+WxYExoziDnQuhM1t1Ac08LdRpohs6bgdLkVIIRInOtTd6rWEKhjc0Yw8NS/DPt25m7CKhtq5UPaVJqDvBaRq9EmEbyvP5zDwHKhlCYegSMR7oxWYbdv3AKiT6geMX3vWWl2wL3FFobbv/SteMvricsKE2ZrltmIiwDiqstfmnlXnXGEqNNNIAoL33strrVlP3F7bPCK5L195whaBYWUtBvQefXYhrrx28ZhJjQrQhu57XRkPHRQ2UQ/c3Hg/jIfUDsTcd8LbvxBS8ocLycfs8lqc2t2dheMMZ9sbePKlsdrFLd9p52zcvPWX7TnZPbADWPpxvj1WLzr1ys8f2+ur7Swthm6Hb+Xj7bQt/3Xhaji07Zlzwz7p5St++dHcnHb9Rv64ewoGaBLT1jNgIKdjq/oLVw3GvHFS8zdZZclJfpB2+LF/um76wxUN28XRixSb2IOd68YVWURRnVq6e2hWBSjWHOc9G5lmWzkvGNu/uT4xnL6Vyfjr7yB2TQ2696dZ51FM0MGebCTarjRBaVLfxvTGSYmDJVvJpFzk6d96mxFg9tjUFhBhtKkTq7KsY114VmznuRr0Zr/273TzAjchT4SSblyh1FVpEhNh1BI10XTQCxG4R4Mh40xFXBVkK1XXKwmLnM9w+0B+OHsb7o5EAfbOzVSZsq78NqvQRRSviDpvR7469d18T8r0lsm5GzYCaJ6qlUBfT9S8+5CLnQl7838UnpuzLF+xeVu3aFdjYdSLWR7DuLJafa/AifAho2Exb/fykVRVal4qYcaO4PIoal18NOK0l28DIkIzXEALDkFwl2MRTYsBkwXS7xFYSNRm0NKg16VAJrpYU2D77ysep1cRSLcYwUNF3wFrVtOqd70GIVLeRWiEEa3FVzVAX67CrCgXO19lA6j7RBSEPHafDgZvjyTpDf8bxC/fs87x4KO8khRWHsly0Viu5rWOCtE0FxfOazVNrVa+8bJ597XzbAUr7HHT7agywTb7Y4ZU1hFAbyPfCrXlk4AahWl7sypv3lxXdhcaHhur0UUsZPNSzeNk7v+y1U+qJqUdW0A7WIu36eWQ9x/a5tpp5aDsD7D365r7tfGVn5LuzaFap773H6smqe/amGls3D79Fa9trbq/crvPm2deoqL1Du7+IeWZPKdppmGGID0s0r+tTLrZ72E6i9Q1I9SjLutXMs9vosJTEBnKE4GO+vIKyAmX22YpCLQuNZ2Avb9+vt6VFaI11uHpyXnp2V6Ct2sg7sp5zwzk2r66oNI6DbV6lVGZMECUvmRwCOuAViT8hnj0vCz/+8WdrKCMOyOGjfauHKrmaFt20mIRzxieXgoFgWqjTvHrTFKOzz+K68Fo89eLkq4n82Y142XUHbRluh64Lj7UKgLYsyzeM4B6GVmO3InCgEsSTDLfB4LTalh2oQii4VLFFCQAx+chlD8u1rZLd++Of2HcCtnlsLezbm+f23G3f8srCPlXZg3RWD1xDzUbZ1GCItLr+wDIvLFNmnhaWufjAh/Y5tvc2UM4WuODEIIV1qswaULR7we4zsYYY4l5UfdMNLr6uXmUIoZGOnMGHz5B3ySoJNtY5BEXIaK3kpVLExoRJ21BMGGs9jyh1xXGkWPSgVW0ao1q+H2K0aCIbqCnBuRsY+69KS8t8aq/X11Xiep0MsNvt6how1QxvCnItvz5GogjzVKHMpJDoQlolwj50/EKNfVkWPvvsM+5Ot9wcb7BSQ0SNKUJFfF6Y6cHNy8I4zxSE2QGfvEwWvi+L6yAYkaTvOlNGafkkrAYP4HE3KzdTLcTX9tz12Ba/7P7fJOkbYQPhZYsovlmo3eDQICp3tAhobKHo5jGlRtaV3u5TdVRXjNTjP6SxAtYP7DSsFQvf7QFtO93v8y8MKPgfrIqnDbl3D7yW3Nx7SWs2cQkxNdXdZVqY3djzXCltevAuGmq9WYqsxt6gkubJ1jFSbH+/7l3rJuX5u7/2Fj21jdt+GYLdw7D+VUC9iSUE5weo2hqohcXTwVqbJp/sTkL8nbzjUGWdUWAP+ywx2hw60WqMbBzbUUU0oUTSztCBtaegtRZL27hR+6r+lbj+TIISgwljBmweYpkLXZzpY1h5Dx86fsFDIqym2ZDIjXW1hYwVU0AttVoIr0rBhChUlVwqy7IQS6FbX9aAK/avuw/paV7ZvZWwjt5pIaesRtsKXvubrWuJxL7CuhV4+LWGXKvL2p23Rw7aBgi08/Vr0kgta8WvefEWmazepi2AdkPdOPWnSRurzba3eRENtEhhPY3tVC23+fD9axuAL/a6qstujw/iA/sPBPu9xIJTO1Urp/ln3l+KBnLZpdgilDV20A+8h/923bD9PhmAKs5YfPkCIi2KYRftyS4CapfPrnnbxxVPKcU3AX/6tp72QJyDrO08ZHuW/WH2qKx6C7BQJaxRijV4ClkMZEyeIuZcmef8tfz4X/xgx+FAlzoLaRXLcdnKI6UqYzZ54KlU5mKRjCnSKtd55nq+0KPcCVgqkIixI8a0jTZyYknLr6mK+miPilJc3a/xp4Ow1n5W45Pdktp9aR6juZgQIyF2HooH0IpUY/TpGt5bxFfWPWRbfEFcVEP9mgR3eS9M1PT37HTq9v7r6TWv1/JUb4VlM97V4YpudSD/RQP/7A3C9gvdrh8VtFi5MM95A+byvrIirAMn1mM1S9pMt8ZPqqLOTJMtB9ZK9ZA1eO16mzCrq3Bwy38B47x7+L5V/V++u4og0Qy5Bu/Ss7+2z9ZOnwaLtk8d2p4PiLc8NYqs3Y0lV5ZqEuQ7Ovx66WwWnpgHjx4l7XN8KuiCNv5CiwZrINTeMwhT7J1LpsyZFPHZ7sJ1zOR5trbpn3H8Qo1dxDju0VtJha2cBS2sM0ZRcSrhWh/1r6VUlpytbBI377oOJ1wXhay75haau2diY3/pFiPaa+3+/96H3/n7ZoTN6D0MW60mvPQGLcxsnraVjFYgyg1qlxK0jeSlU/H8vS2+5ula5LL+rRm7pfHKGv6u2yovXON+T3txJfaXzW/QWm57z6uzP933Lx27z+kGiW7l1FZvX++L6Fr+XD3kztNKu3PSbHBbB5uBbt9t19jui4h9fgmylVnXP/FzWYUhzOxboYL1XphzMtxgd12UNZx6cTna5xfWDssYAkW3Mt4G5rDelH0EvM4sxFq+Jez+XRVZK0sfPn6hxt6ljk8+/ngt2QSBcExoVc6u/zXNmfNlZFoK05JNy10hq4lQXqfFdNy7iB4H9+qJlJJ7dns0w9+3Fxmy66IKXqqqvhBWlB94PxR8GT62WralFviG1VodEQdT8F3cQ/K9XdtLN/aY/7dbSGvsvXq69quweea2qARfdtU2C9dDMz5A8c2iWWKrY7dTE7sO2tzIFgW057TwsuZCXZwANS3Ms43atpDTav5BLIoppaI+HoogxNqM3VMt8+2+sRs+E92biW+GwVywk6I8aqg+QUWq+9WXSHgLy3XdzdrRzrkZtq4qNqskGtqwVbuNrZy6sie3iGefNURPoYYYiRJsrfrnbboDgvXkI8JtCiQEve3I9RXTUvjJ+cp5XlxhJ2zde068amnMNpqschhs+uwweFUZEzb9msrbL9bYY4q8efOG8/OZy/MFghC6hCpclgtLmZkWG+s7zm7sCkWVxbXkp2lhnGZ6eji5pFM0Q4/JhAuML7zl8HZ4eBkazzyuHsE2UlkNsa13tw9bzGuTSKQVvcWVPNfqHYIQzUCCYLO8NgNvrK6f8j3ajOEDx+rRnJTquWJ7+rp4WyTQNpVQV0kqn7qwuSbf9NYP1wrDP+UU3PN5paAu1p67uNEXH98Flo7UoJiikBeU17HG7W13Pt69mBm8qdHGKmstXdQJTO7paZ5TWAUe12CkOe5mk+vG2a5pI/Rud7wFU4gj4mqGWbXFQbtNYCXviH+/RXjiry/OCcutBKmNSqOgZuwS4CYlegkICQ0HrnPmecyMNVNDoEpwOrXl/xb02g5kI56UMGDjt5PQ9dBFJYmQdmv4Q8cvfvyT784pmcxTDNaFFYJJOCkbB948le3wxRH6xpG3XdlCmKqsOeOad+4NfW/IOxe7R6vlvQvVwLhNk2674bS8cA23oAWUiHrpBM8nm6uw5zSGWPvRdjN3DRvNOHa59vr+a8y3GfqLo7WCrufjIf4u/Lcf+7m8qFO7a20Qs25L2ohJHbHr6Q9HUOhHkxaDwtIrSCXOZox2HzPUYNJNvqk0QtCmXiNU95hVTe5JZfPYodp1bMEHIkYV14pKBSntE3oZlB2rZXdZ1gu7nZrtb0KouESzfTbDGb0kWFsgL2so31ILffmSrFvZdos2LkNDHt/vKGx7cfG1qXG928GFP8TbeFXMs1vrQ9Oga9UhXWnEP+v4xZJqqpLnmSiBw+FACJEuHVGFd88TcEYVllpYaoGYSDGaN5kn5iWzlEouphlRMVptzmqSvcXzsAbMiWyh/Nr9ZQ8Ty7ULuvna5h03g1njohdx+LbL2x83ILAhrnZjV1q+fyMpIdH03VfOfgsLWh3K/3wXVuzed8+u1u111XwXYAvEjarp7IsYUChrSCBQvOTXOuEQG2si4iNIF/tbP/fYDYTUQUzczQt5HgmhI4TIMs5oeWSZM0sV7wuwKEBVmGtBJu/pT97u23l3npqSTwhANRAzYNNcBAtNI9jf+sesxdC9GBVNlSCBFHrXvNv2KqPx2QVdTWDdKK1ib3hBWD14oPEBvMQoWGOTNgo3bW/2++2xwpqC+Qa2vpdtgg1Hsb5G29hyUZas5AXyDGhEwoCIyWJVzymaQxDnbXTRBDNjVGwEj6fE8U+UZzcKq4Xe0fqJm/oIrc7awifztqa+GlZv31DnPZaxzQZvHq3FeGugt91u3f18Xfw7c9+vil1ksP5bhJdXdPf9Ghu+OOXdz8xgVy/TTnT/nPazLTN8GTysL9uih93T5f2nrSGCRwlbeLr+ev2LffSye519pKSmIhS7hGrvrbWRkgMhCcE1Pm2PacCWOHHJOreEum7ICNRgRtQuR9vv1i1Npamrswc2VD2CWDkV7VxZ6+FreZHm2Xnxsy0a20NxWwzQvHTd3dftE+zuhb78+uImfMD4GjSy7vHeayUqTv/dPvMGI7WJr+xS0935CC/u3YeOXzA3vvD8/MzpdMvpNJCz8vj0xJIL7x4feX5+ZsxKSJFOIkgHJKT44MXigpOOfle1zrlcKksuhkg6Km9oDxuxbNuOd1e6hXJ7r+df22axAloe4kqTRd0ubgN6tr/136yTavw3zTUpUPx1V0NX1vr5fkGu3kE3y96vWw8pxRe3eH6ppbjy6bbQbTpKZev1tNlxHsy6km+j+znHPqrR/PIMdUHLYlNX80ytJimmtQ0+sHnlqbOIqlYz5KJi+gW4oq2K1SBlS79UZWWw2QZn17C2f6sgRTZjtm4iqBaNWMPMRkldL0y7jeu13DZ/9QVQ3ZvbZu3OotXSW+ge7MO4X/J6tufwut3l1pOh7V3EyrvmqDz9k4ag4w8DKsOmObZeE5sZZ2sm52yt0IuwzAJJCH0iBbEBpfKzy27wzaWkfxd4wmKGrKp/UUTeAP8H4E8Bvwv8S6r61de9Tq2Vy+XCMBx94spsI5HHmfP5zOV6ZdGAxN4ojnQoEQnZmHXeNCAm8bLqsZViG0GtarzpJmH64tgbu6uuyBYtr6UVv5n7qGA1+vXrvkgNrad5/VPcsNfXef+jNGNTNhLKztjXC9+sWtit4u3pm+NeGXetVq+1Ul3m2MI7Aa9ns0pTbeRURYkad+mDN5BHBY0W1ldjnNWS14fWssmAuVBiSvZ+tQYz+CKObusWmlZFqgNijSteLa2qzdjFSauiNDktkdbiUNefrRvo/tL5xVn3annpEdXvg12GfWRjG0FsiZEzDbVulF5zIrJe+xfxgwuatG7MtUUYF+XwdaWYNy8VJyex1ZdfRDimsrz1ImRKEYumJBKILr6xp/d++Ph5PPt/RlU/3/37XwP+DVX9KyLyr/m//9Wve4FWZwe1wXTTxPlsYpHTPDlrzqmYCkvNzFqZc14pjm1xZlXOS0ZD4PN3T/R9omjm4fUNeVGG40yKkaiRlCYkRNNwaAYTrLe9dQm9j8RvnqHtCO4Rg+/6/jnsduy8yB8SSuG0UF7cGEHYSwr5XW9PW+PE5pW9BNfUYlrfvih1zhCUUmZKsQE9Xe9z8lbMQtjYfG4Uog4AbRejkXPae6yG7eOL2ueUhhOItYbWaH8dk0ULwT37HjQz467UIuRcPAiygZ8hKBoMiGpafasXFZyBtuEX2s7HLa+BVlvZs5FXPnA79vfbnr3713Z33g/dX4Tz+7r6uum26+gVjcquahPWSGZ7WCwvPuOwraOWWJgib0Rr8vRFVxnsWgNhEPomhf4zjj9OGP8vAn/Jv//XMbmqrzX2EAKn0xGoXC5nnp7P/OTzz7hcRi5zNRYSkaVGM+Zp4bJUxiUzl7Lz7IGpKp9dR9I0U37nB/zwh1/wa9/9lL47cHd3IoSEZmU4ZU5iWvShPyHRFVZbbzgdtCEJu6SrhcXI+6G13TVbRh7OB9khobtdw42pvex6C1U8pG4RQMsnGvUK1i2+/XH1n62eeXsPwbu6tDJfRwPHaiaXxdRtTgekS0jsCMmajlbR2KBoaAquPreMwMqi82tgKjUWwtcyU8sMaoopEqoJLyah6yNBEqVYhFWrkKks6imGe1HzgJgsNN7gQUFESVHokynOhCFBitQCJdt0FNN296pGXaNvV0CyGr6491/vzxqktfuzGWtu5UW/S5sU109HDPtD9stijbR8cxLA9QYKuubltQZUA6Uqi6efS6kspZJqQWr29dQYdraZBoE0DEBCZKaUiVorT49XE758uOH2cPPhHc2Pb2rsCvxNsa3yf+la8N9S1R/6738EfOuDF2Q3JOLThxsu80LfQZ+CD4rIqx66vZMv8FXfrYlJtrDMy0AKi7daXsaZrlTOl5FxzAy9D55oarOlWNhVDRy0GKkNnGg3bs+kks2h+12V1ctCG8i3ev+2m+8uln3dfac/7fUtddilCj9rYe2wBm3FYGgxsG9S3jY8L+S8ULWYnnsINh57ZbBu+Wj7rFZ52+UDu9o268L3IRyNBrySTVi9phU9rHnH8s3gl8ZDcdr103WzqorFsuJG6t1mRQACpVr5rRmLXQ7fjPy6qF8jZSvb7e/Ceo9fXH554Z71g9ded/9/mQLo+0/b/eAFt6N93e3b6hvK+70FTUWnRftGFfHrog1t30TA2sdvjurr2HPwzY39P6mq3xeRT4H/q4j8vRfnqqoi8uHLtRsS8ermqP+Lv/n/4j/1T/4G/7E/++sMQ+LV/S2HvuPxPCHXmVAqc52gCl0tdE4BPATIBIbbOwM3lsx8HRE1sYSxzozTzDRNTPPLVr+2GKiuQVcDlM6v1gIYjCzRBSAaSIWudtVIOu3iuot+33x3i8dJILA1XeAGr+7EkZcG395/ReQb0br9gRucTwmtzmKrpVByppTC+fnMMs+etpigxyAH4oB12IUOwWfYYUCaxi1HXgcM+oZLMUnsMk8s44U8T7aZlAyY0EP1PN242+bNRTeQbbcWXBvdzk0cu2hNRNYEUpmDMCfLRbUKXbJ8vmR87hn2Xt4MtuKm3u2m3m1GsDlx+/p5I/ZsBdfdjt4eLwzTozP4Kd6RbS67n/nrt3x/LdUh1sYqGLMQo8kaS9TIY/OS6VOiZ5vrllKkLDPLNPk0HRMbjakzHZYo3N4kUhI0j7x9/MrHmX/4+EbGrqrf96+fichfw1Rlfywi31HVH4rId4DP/rDXeXcZ+b/87b/Hd97c8x//D/8p+hS5PR3oYiD7rGlQ0pJRlKSFpCY91QUTFJD+CGlgGSfqolAytUwsNfswRZvCacjuFlJrq3FIi1/dAmsGgnEOfZDACqJoQ2yhSfavm7g2w2gLdbcMWg3Jn7w6YtzYd/XfhuZuunfuter6Tmx/XUHtfLVW8jRRcyF7q2nJhfO7J+ZxJnY93XAkdZVyqEYaibKi120Q4hqxryScdpb+fhY/+1y1ibzMq4w06FpqMyMMlODchvpyG/Sz3VqEV0bfusbQasq8QYSSbf5eDB212rjjUmz66zIYSo0arzCImtgj9rZSdaXuirT7b4b40vk1i37fE+8+03o1VnRjxQT3T3ebxuk9+yyL9ge6exRlDeNztpHSycI/w7b6jq5LjGVhyYu1gfQ9QcTGRA2Bvo+8enWi7wNvv/yMp8fnP14/u4jcAEFVn/z7/zzwPwH+OjYc4q/wDYdEtIuiHha24YqquiLrVfEb28ISM9oUTYCgIFTXoQ4hgUJwj8DKTtMVFVWNrMDWPlFbvfN75+s3R3c13Q+fxftB+/71dfdgJWqsAZio8+p3G0ZDb3b1NG2iY9pm2BVqXlimycCZy0iZZ/JSWCbreFrGiTxnYuxIEknBZr7Z/DOT5NqnHGsNXXChBTWLqaAlo3lG80JeZpZlpi6zhfJ13yO6Zxc2ENDDVF3viN0bLdumh3t/V56pBNpYriVXSoA0GVZQa6DkQIwwdBWqUFy8cw13tW08vm6qXevWL2tDQDaMZGPFNQRg3zG3u8fa+g3aPWsGv3E6mpq5nfdOP34F9+xvS63u2Jx2nAtrOZmNa9Lep0uJ42FAqFS1AZohCUmtlH25KvMiTPP0oir0oeObePZvAX/NTzQB/ztV/Rsi8m8B/0cR+e8C/wj4l77Ba7kTbLl6odTi/etqNceyseGq1yNiiBxiomrgslhdXYuQYo9IJFKcOebjoNWG/pm8czBDAWMivih964vPtYvPf+rX8PJXDal+YfQtx91eEAGTTlr/znPFxhfdyVRvG4W/rCq6ZC+jmUfN08j0/ETOmcvjE/M4keeF+TpTq2IzKpQ+HRjSQJcG+nSgS4PNWpemi1dYu/QaH6ANZaxWE9O8UMYzdZmZL8+Ml2cbIrnM63PMYA0QMPqmK9hqIdds99HPsaqr7ypm4FgZNTh1mmypRcmFZbbpOWWZiKGgNVKLl5k0MvdK18EwWPaj1RtCopKiBxYu7xzUHkbS8nPeNf+ID5hYJaFaJKhqEUhgBRdfVj+FGg0s9Qqdz78rLl1t52PLylh685y5LpnruHC9Wg9IxRyXIuSqNrcOM/bD0HPTR0pZeHr6gmkZkZjoBktVp/kdUCBPFoV9zfFNxj/9NvDnPvDzL4B/7g/7+w+8ooMThf3Y5Lb7vQ+v+AZqwI/vrOp3ZW2PlX0+resOt0lJvWfU/k3rhX7p4fW95/HCntecVuRnPF9XL7LFcW1faGfZztHD5Xb+buD+Ahad+ESbspgufZ4XlnmhLAvzOG/GPs1+mrajBbHcL/oYqLX01rwS2+dZT3EHyJmE9suaeinZRmPX3TXdgX2blw9r6LyKNojurvO2Sdpe42GutFJoXevxuajXl4WaLU9fluoiKA5zqEEwoXpQYtkJ1aOplbHmEdMLBJ0W3ruHbj9ut9g7GD3C/tpY74M/fM93rFGsa/etPR201JHddTMHZgIVds4lWAqTkm0excedWXnuA6Hq7viFN8IAzMvCebySc+E6zyxLoaoQUk/USkyQUGI1TocQTL9rF+XSQp+AMZSAXCvjPDFMhgHoe8YmLxYzHwzj12PNv3CBC33vju46r9b8Wnf89kZR3RvD/k3bV69Xq38L4DXschkZ3z5Sc2a+XsnLwjyOXB4fyTnz/PTENJpM1zJnYojcPbzmMBw53Nxy8+rBxkOdDtD1RriWFkk03EK2jKN5dgflNE+UeaTME3mayNMMVZHiG1TBWGVVsAmrAaFHpANZqLp4tG9vYJLYltaEaOF7TJF+6EGEEqunb4JONl8gZ5si24ZTxGhYw7xUDkOgVhuBHKKsaWBLS7QFLtqIOL6e2n0Tw0iUltp4SqNK0yq0KaoKQX1o5C7dVGO+qTZyjP0sRBsE0jQVfTnY6/mbVwJFIXvzT1EbDVYLZCrX60TJhbvTwOF0xIaFKrUu3D503L3qqHXhOr4j55m6TNR5sn6Dn3H8Uow9l8K0zCalk625peL101qJoVBiJZTgBAL5cPTtajdNbaa4bt2cuw2o2FCSnwqxf/Y+DWbqmwfX9v+2eawP3UJx30ikebP1L9uz90WTduyMfX24sc8Ly9mMfDwbyj5drzw/PpOXhefnZ+ZpWhVjUtdxd28jtrph4HA6EboeepfQDsLG0tsbvayfnTaxtZrB17xQ80LJC2UxZdZoLspP2zYzbaUwMXwAqVtWs4ZpxuYDkGTGnrpA6pMj94rkyrLYvJeqkBfr465FV9CuT9k3GHU9d1iyeOBi02KD6NpU0/a0VVwYWIvzK1MyvMjBg5Of2j3WYl12PxX8uLG3rEaxfo5Gm5AXa462Ymxv17ZBiQtiipcXlWW29O322NN1HTF0hKN5+NuHjvvXHbnOxOfMskTyKCxhB0p/4PglGXtmmiaq5+WmThI8nCpM88y8ZOZcmXNBQ0eNnV+kn64nWlpg6jZL3oCPnIuP2d3KYKvxb9d+90L+Y/E7+eJ3uxDh/UPdQByF3+rI7Q08cG9p+ov33VUG2iLKC1oLeRwZn6/keeHyfGGeJsbryPnxTM6Z6+XKPM9railBiamjPxyMgNF3SOdGvpbUdu9L+8OdsYOt3GwSSerGbprpLaf3P10qZanOpA2+8I2002D+1qiyKtQ6jdhmy9t0m+iC6yEAMa56A4iFuqu3dwXiJStCMWruUqkqdIudRxuRHEKlxwY/xCgrx6A11oQGJqp/1pW1tgPUWg7Z8vw1JGiluA2tbx5/XVP7Naa2bm1vlPW17Cn+OQRMPtpnylehFGWaFs7PZ1ISjgfbs6/jSP7qbEIlITEMJ7rYcegPxPizTfoX38+uyjzPPD8/AwGP0kAiEhNFZ86Xi9XMq7JUkKTEw7DlPCuea4u0ze1alsw4Tgx9ZJ5mljmT+0QthdaC+jWfbPv9SsuC5uHV82hz1PZ1xbTr1hK6odS8Z9W7ZFH2iKu/niGLUJUyzZR5YXz3zNPn71jGmadHC9nH65Xnx6d1w1xKNg28PiGhoz8cub27Z7i9RW6OW9tq8+It5WgEmhf5N/Z9zrBMMFtoWOaJMi+U2UYdNbQ+z5UyW+idF/NMqhFLwopp4dfGXzevm5Jt6rGPhBRdZaj1rhqZJqRioXCt5JKZF6X1rFeE61SZl2rMN4SuE0IHuQa65LJlrs6cogNw0So3xVOVGExZZm15XpuE2+0Ku+vkm4VEC+elDSHbjLiBe77Id9FSe051Yw/WKy/r6E+QZOBm6NYW11IytSjn5yssF/ohkj6+IabE49Mj55+8ZTj0fPd7n3I6HawVWGwk+s86fimevQ22BxPhs4aANnBgGwnc+Ntr7ith3TDbz9oFZy3hbfOuN5DO33d/O1t0DbtQf/v3e7EDG7PM3/uF1/fyWIvtXnh13b6uKI/SaLgtr2x5KVWpSzZVmNnEIRZ/zOPC7PJdpWRy9usYItF79GPqSH1H7JKPr9nhBdpOvIXvrF/XX8FKV9P3HiahjE9MMD1Ae7CGoC9hka281Y611Lbjq8vudyF4W3OIPvTD6/0rGcY6yLRs72/z9qySE5xaamvLoh0jt7R0TNZbUdttbBv7ByNg2X6x63pZoY52P9u93KO569pq68nXz+5c1ueJrNHtFgYakLfkQohtWoySF1OSlRCY50LqKsToykl/wsL4UquxsCpcxkKpMC/CkgPXaaZqcQQ+EAmE1JG6ASUiMWP6sLSkaZXvyVXJuT2qlUBKXfkhfqW3D1Ix9MYjBEuYZAOYdxd+I9V58LVPRku22e1rHO6vvwvj7d87QzOlsm2TypVlzNRSmc4Teco8f/nM0+dn5uvC47sL1+vINE+cLxNVK5IEQkeMR443N9zc3XL36hV3b16Tbk9I58beUozdeetSLA9V4zUIPnUUYJ7QZUHnxT36wjIt/vmUmi2aWqbKMnmIXRNb73pmWaqBVh5+Q3TjDn4Zt9JqkIqIhfSJRDkIp1NgSYV5mqhOfGrDIOfZJ+n6Btt3kb4XlLh62KhCmCox2zVuE7PE9dlrwYBGIAbjaEht4f52y2wDkxfdeS+MlGb4zZwrq1adsjoc4xw45Ubi2vZq+6Y5rTaIw5adRRaFwpgXCsLjU2ZqUc3SkafKP7j8mBCF0/HAzenINP0xGXT/uI/m2Wv1cVBFmWaYszLNjqILHrgF15SLqCTb6aV5USyM98tflXVcVNl1FG0LfWfsu3B8NeJqHrxFYVvOZqyol55REfxz2CD5XTis7d3YkzfWv9UCGN1UHdkpcyFfF0quzOeRZcqMzyPj08w8zlyfZi6XiTkvjJNtFN2xIwaTse6HA/3hyHA6cby5gUNvVbh2bivmYF9qbUQdiygEbWK9FsZnJ/G0Ry6UpVCLeZZalWmqLLP64jblm1b6tPp6e1vPS9dL6l5WW5nUNlmjg0ZSZ5iiUEmpEuPGSKvuwUu2dtr2uyUrKauX4yzxWrJ9hhSVLusK3okbYYs9wCsrQbcgwi+XbVZmzC/hnl1Uua3sdY3sL7nuHi8Ymuyuj7/mKoXmP61ANYiecazU7KrLJZBL5ukrS+nu7m64vy8s+WfX2n8pxh5ipEsdpSoxeR+0G7AIdF0iRBASgQSxAzeYUnUF3SwqqkS2vuEVP3qBiDtI1gw6uBeXYMVZ21YtUvAcHYXVHbQXbZd/V5ax3xmQZc/Y7vD6/mthwEtWWqhq1NDqDTt5KlyfJ0qujM8T85i5Pl0ZLzPTuHC5TFwuE7lY9UKCMISOru8YhoHheGA4DsRDD0PnTBPdPkjLF5xJ2KLjWgp5WRCM/CKq1GmkTleWeWY8j1YFGBcbQlCUPFfXTROaxFeQhBKYJzWAtGwtxJFk3jsIMbn3jI5LrXmzb0C++cVoE1yGQ49qoJRKzvahxTXuSq1MTq2el+JTbqGrdr9LsfOeBdC61qdNd3TrhLMpNWWTKmDvExojc/valpQ4TViVJh1nK8Dzg+hrtouBIUVSNWckUnh1E/jeJ0fOY6V+PqHnAixcR4toU2c8eCETpK4QQG3RAoAEYrSuzVKFy8WIVT/r+CUYu5BixzAcyKXSTRUoiMzUWpAQOBwHWzi1Y9FElcRCcK9dWXw6a6udhyDWxBKC98Pvdlbd8kNgC9drG6kp2xb6XtlC1ngen+7gIXhre21gV54N0MIWh6eMa+Sx9bL4nLpqKjJa6zq+ZxoXnt9eyUtlPC8sU+H53czjVyPztPDuqwuXywUVpQYldpHUDRyOJ043J27vbjnd3RBvTnA62obmUlCbKJusBi9FIVfqYnpyWivqVNh8uZKvXgV4fCYvmcvzyHiZqUWZZzunIFZTl5CIaUA1sJQr56v1OFgpqxF7MGPvLIwOSZCI4zVevirV+fGBrrO/O50CqavM08I4TkhW51ZYi6ix9AKHazKjDckGNaqSMc58znC9FkIUZ9wJfbKHhea+nty7C7gyb1tkWzjOGvUZ9hCS/1y8D79ClY2Lb946gCZTUpLCXDLxVcfNzT3PozXClDxzXTJPTyMShJvbwQdOVoKYSnHRYMQh9VhWAl1/ICrkvDCO1z85QyJeHq0c5fGy87Vbrm7j+wJBgwtLtp7gfeltB4DtQsNN6ug9oO0FeuQ46ir8uHn27fmsEkf7lgi85bCBcZanmkXvAXvapuM8/yb8UGuhLGbsZXZZZv+aF5u2ssyFZbZuqHmxqSu5VGgdasGm3qYukTpb4CmlFZzaMIifPrQqecnUydphS87eTWfKMzm3z+KfZ7HpL9Zu3KofQLCZdtaH4ICjX4t9dGo9M+3amPEExQcksuXBO1yhbdAxCUkDtQQLzzWQOh/g6e9rNFPXQ1gKy2ICGgFMmnqHebk2hKd4tn7aZRLRbexUW5q0CLEBvrBvjd5Ws/2B+t/sCZYtddlrn6Yo9ET64qPevDRaq7X4tvN7P/366fdtjuynBTbeP34Jxq5rPbx4vtg61FKKVAnUYG2AuUSkJjTDNC0sRZmWhTlnKzNEryFrABJFhXHO9POyY9C1he+5NdmTJ0fcono5xELYNi5awSMGv/1a3Gt7/Lsi7wqLNYvsvThNWae6Jln1uebeijpfR2q18N08e+b8bjLPfsnMU+Xx7cQXX16Y58xlXJgWZUiR27uBfui4fThx93Di/uHEq4cbhtOBVBe4nNfTM4vpdvGpkq8zX/zoM65PzwSX1BPUVFJUmZ6vTM8X8rJwfrqS58x4nZjG2TdTO8ciateTACygwpwLBEPti+ft8zSzZNvk5rxYuhZMlKHre06nIzFFjkfz6LaxezUGoe+Fvo90fUcpyuGYyFmZpsw42qZ5vi6cLzOXa+T5Eum6yMPtQN8Huhjokli50NW1xDcgYC2QS1BvotkFeaJbD9WKult05HtAu9Dr34XWat+odutMKLUWVSBUm/fWpLXNjWwuxSJYM+TOUfoYjS1o6r328YoWqioxBVMA/pMyn70d6uG4IZTOAQan+nkdEkE00KrcuRSWbIZTq5Vb1EG8VYASIZdt9lh7r3XLcwNVQ3lsJ0as/xnM6DesxLy9h+qmjlp3Bq8rKKc1Q3XOeMF/ZptMrZWSs51r47cvC/N18saWSsmV5VqYr4uVVa6FeVbGceFynZlmIxgtFXoJpL6jGzqGQ8fh2DMceg6Hjn5IRK3oMjXlA29ySTupO6UuhfPjM+d3b+n6RH+wWXNNtSvPC8s0kxcr9+XF6Lh5KauXs+0he5NLcHKUiU2si9eB0mlebKTzsnCZRjbhi2qGHgJd13E42DDDNZpS6Drz0saZj9RqvfOlQIiLaRPmwvW8rD39pUT6PjEMvekUiEUHRve3aKwECGXDV1p/moXfzZtuvnK/hBqk86JbX3f/lv3ftPXXNhEvPRJcDekl0NfeZ+sZ2UC7sBuK6ldoxRJCCI7k/4wQgF9aGG+5XK0L18vIvGRTIQXL/2JEJSJrDd5AnyW3co2dYK3GcrML0+bAFZaS1114BdXXsLoZfGZFyWtAYyuoNM+uNhgyNhTZpnHgVIgVGq4KPhppQwehZEOwG79bVSkeDltuClqtb3uZmrKOo+POGmtc622/shyzWIs5eamm1T4vjONMVWU8PyMUQowu+QxTfnZg00qSl6dnfu+3f4fHL78iJtOKSylyezzSpYhUxzB9BJFRUxvxpDHaHBXWgrHm/Cq5omwuyjzbyK55XpjmxSaauFdsXIhlKcyT6cvnuVBioc0DsEKH1+/rNtAxeNidUqDrEyEIJUdysOcUv+bznM2JkOiC9VFUN4ZatlaEZm5O4FuxzGanzVZ3Nkv7dq9Ks0tCfC3tf7LtvRGv+KKrA2luZJ15QFh7DvD57TnrmnbGkEALUrLlJl8398mPXwpAJz65tJaF52cTnIx9R+w6ogQTpQwJWZotFcZ5YfayQ0PASjWUMnv4OZfCOMMwB2NK4Tsp+0DL2HalLoBQvWtOXOzPoq9m7BFJDii1ri1jleAr0XbWZUHn2Y3dbnoeZ6sHa+tMUs9/N4xAa2CZK9M4G8K9FC8reS9KcZqvKk0BtVYhL1b3n+diwNU1cHm+sMyJvhPqdDWU/jhQSuXd2yemcWYcM9frzNPjI3/33/n/8sXnn68lqMMw8O1vf8LpeOTV/T2v7h+Mk25BCyZyaYhaXixSWVx0ASIanKOATaZfcuE6LpRSuY4Li9d/26ZgXIhCkMy1m8lFOQyLLeIWcalNR20S4SFGpBGtKvR9oNREKYGqPTEFajGsASwyqrkSVehDQuNWQs3oGrX5SAcSu85jN3jdbbb7MtnmQN8XG9v+3RCl9g/BUsMkNgySXFC27k8kEKJJeKtGN/YEklCUOVsfRNcJfdeZmOdinAuabNgO93j/+CWF8S3EM+LLkjOhSxamhLBeyGYo9mg8d/+d/7+lRTbLXSyvz8r5OvP4PNJ1iXmxMlCI1TS49+avxUf0+Cu2G4w/xcUUNDTQpa65+sYuK1YyUvNA0OrYO15+25T9OZaO2IIv2bxl65wqnpPZFFvnEUQhaFi9sD0CKYV15n3wzagW6//2Xsq1Xp6XmWkcWabZQtuYHDCstkCddqxFUWfzBQlEsfx85Y5rA0rdAN4Ld1+kTvhY6sZfddpySvaEGO2+m8BHi9zExzFtefIGmDlqLmK9ANE2hhjNQNC6ee/arqvjQoBGZ9OpbgbNlr1Z+qisfIs1fvdPoe0cGij8MpR/8bVdC1lPe/3s7XcvHsDmmtgiutZ+K03qa3tPQby19R8TQCcir4D/FfBP+6n8d4Df4ufUjffTp5TCNC+M08Tz+cx1nBiOB1OelbgSCaY5c75mzmPmch3Ns4dkw+92zIfqOX9drFZ8zjP/79/6Id//7JHf/NVPLEQ9DXz0WjmFnkbWUaDm2cffOn9aLHdXwRK74u/lqG5relGtXj5TK1kt5sWrI+/L3DyMYQqmyRYIQRjnmbdvn1xOSimzGfg8BkqxibbjtXCeMtcyU6gcjh1d33N7O/Dm41uGIfHmo1tubwcOp47bu97aP4NjCJpW9ZUogShCnmae3r6jlMKvfe+7fO8732YeJ6ZxJIbAaRjoUiSpkK8zQuTYH6ELnPVKXhTR7JuRRUGtT94wFKsxF1U0QOp7ogop4RiKGwn45liJMZgiraNa8zTRjL2JW0Rpm5nnuN7YkjCxklgEkYFalOkqjL55LUum5kIXAl1Y6GIkSYdEv7+hbfK7RHy/T73YBlg/u+junjYwZJfMb0CeV25wsBehtmK+yDaavBQHcU1Ew9h1rGCoOh5w6Hu6qKALWhdEK0MyUZeiQs7wdRb/TT37XwX+hqr+V0WkB07A/4ifUze+Ha1WvuSyasYhQtd1Jk3kJ7rJ99hzclE0OYC3K6utVeQKYbHX/9EXz1wuI6fjwNN5Iojw6s6MAL9FVTHllaomidwaYJq4pJoUlois44qasddarROsVgvHnLbbCD+bTpusCGnbkWtVxuvEPGfKEqjZpJKXYgMV5gWmpTLnSqZSpRK7wHBIDMeO001PPySOx47jsWcYEr3nrmH9jA0Qsve1ck5lniZEhPv7O7qUGC9Xruczoi2MFaIKdbHe8dR3BImMYWbVb2/AqrQGEd8MaS1DFpLGaBTaGJwyq7CfsrL+6dqro5ScWYdwSCBJNENZPaK9Z1AxCWWfb9aRvA02WRttE4ZwcLfkVtLChWlbZNfqbv6/1XO/X7Zsd09efv9TZbhm6Fu0aPfB/yJ43Z2XfRy1dWX6Jqdtb1wzfyHFSJdYo1xQV+4RI2V+TQgP30yD7gH4TwP/LT+JGZhF5F8E/pI/7V/nG+jGgxnYP/riif/HP/gBhyC8fvWaj4Jwc3tr4Z4YbbJTuOmVsc8EhfmmZynKWIS5brO9AUcpfR4cUFr9Vbffh7aiVuClMaI8FF93eGmxlhlpA0yqtDVtxLpqenC1FOqcqcvixm7h3zybtFJbUIqwzNZ2O44L02I92HkJ5BxYlsr1as0tz+cr1+tMrpnh2CEB7l+fuDkN3N4O3N0f6IfE6cZR+ENiGDoTfezMS3Z9b6GzBIbjgRATr3Jd13DfRWIQhi4wRPOqUqpNavHJoSEkki/uIMGvY7CQGW3Nb57jth508+xmO962vApstmtvSqnRa+mrKiyNRek4SoAQXVxyJblgJVcCSLEOtGp/U4NSukjfdRZxNZGNal5eq7LEiFYTwOiSG67jOuwbr94nWGFRktlE+8n2pZ3futntXeyaKxjjTWKEKVPqTPY0auVp+GvLGjAoOc8EDJitAdDsUKlP2ME2kxg2pP5Dxzfx7L8B/AT4X4vInwP+NvCv8A11498/qip/70df8vc/e8tvfPzAf+Wf+bN8++HG+9ezLdQhosDtoCxDZog2EmouwldPC2W0RoicMwqk1G8yPaoEbbO1Wl4YiTGsNU2/ipbfaTFEuQha9tCK0Xpjsqtuo+OELhmIorVQl9lUYqaFPC1eS8eN3RoWrN5sjmKcjHK65Mo4KbkEpjkwL4Fxqrx7WliWzPPThfE60h8itw8DfR958/Et9/dHTqeeh4cjXRe5vTtwGKzkdjj01h/e926QiRA7JCjHU2Q4VIbhwP3dvaUgxdhy86FnGgbjyY+LzWHPYPhlIEpExXCBGCNVq1VLwPHj1uJpOvwNQxHMoPFIjRaJ+UYQQ6RLEZwqDcanx5UmbJ+yXDxEI1mtHi65gGYxaXBjzpnR15woQ4+WSlks4qqqzFOmxsoYhK4EUuzQ0nml19FzFZrEt0E7e6M1Lsg68ntbJhu+s2YCW7TQcmwhQAgGQqcOierRbTag2XGC9vLrRFo1XEtUyUVIAQKFSF2DiqpOzQ1x+1AfOL6JsSfgLwD/sqr+LRH5q1jIvh5fpxu/HxLRjlyVXAtzqbRJrSEEb+oIJF9MXYr0XaIghLmFToaaSLCbblGXhagBcAGTFyCbOLqzzVrfl7P2vOf1HbAdn7W13QRdxNdiC9t3j9ZBtlbl1NlmNsmkOhq/LM4XqCZlNGdlWuqqH74shaUUci30IdAP0cL0ITEMkb63R9cZSBe76AIQ1uIYXC9eQlwXpkQPzzulq8bkC9l03bRP6JKoOViji0Jlk4quuqAIOedVJNRCT4+u/Lq1KFK3QepbxiuYp0bNIbPRl7crvvWSbVou2l7U/x12Dte5GcHuTRAjpTRZa1VxBd/gbfutpFlXBp3i9ryG5g38quvb7wdcaPs8O4Pf6uNKGy75ElSUDWBbP/Vuje4fu3PzQty6Pt+zKdNkVFvvgTZa4+uPb2LsfwD8gar+Lf/3/xkz9m+kG6+7IRHvbwharV1xXhZCMMncEAP9wT7W3Z1SJcGl8MVl9Flw5om7fuDu9h4Fnp6eGccrjYAQ1Hj0FVYRwxBb/O0XulXT1+ELnhbsNgpRa/AAqMEuZi7eklgrtSm/LpU8m7GbGIeunr0U+74U5XKZrBxVhTkncoW3zwtP58w0L7x7vhotNVtb510/8NEntxyPHW9eH7i96Tgeeu7vB1KK3Nwe6Pue2CW6vjdj7yxMVGRFpYkBUbUN4tCjtVCmiJZMiZGcOsq8cMmZrAtTXrherpSqzNmqAtc5My6ZXAvX2e7F4g8rXvnQiXSA0KOEVWIpSLSyGaxy2oYtWOkJNWTJRBU9Zccjr2rAp4S0DrbAN5oQoBOfmVbstUJQuk7QGEkxQoXidOSqFR0XYhC6LnI4mqxVFOPuR0kWydRCySNQ1mEMVZVcHQETBfHoxjUWTJyihdbGA04YWw4RKxliHI6qjltle7QwXh34ZTXyrQoknt7GKHQhkII5uuA8hFpseMjXIXTfRF32RyLy+yLyZ1X1tzBF2X/PH/9Nfk7d+BevjToaaahsjImYAl206Rld1zEMSrfM7bOsXjjEwOFwABHO57PPfRen28rLHda1yXyrhf1O3fbaVkrT9ndtsqZHAz70oLLbiV94d137a6rqSgUu2evrTjKZ5kKtgUUtvJ/mYlTYeeE6GQaAqeMjEQ7HjtOp53CI5tkH8/YpGR++65Np96Xkm1qiybQ4W32Dkzy8pgSCZmqGUJVYlUUN7CmC8+NnclbG2WrpU64ecZh6jOmfV3Izdpt0QQy6qcW2ddfYX0D0691m05nxWIutBQAt1XKPWSsavC69+rpmENuMvcaAC+Lv7yGFCj4D3s4/UzexlHY9WklLnEuAOiNakMT62qIN2/FwTy2JUY8qipt7U8Ztht7AtuZoGgmsTW/dtOI33GjFLuwCrmu3Mel8Apph/cIqP/11xzdF4/9l4H/rSPxvA/9tDEz9+XXjXxyuTBIsnw7BPOY4Lp7fQd/19J3SpcRShL5XhhoY+p6hN126hkArLc+xcC0X28336igNfGs3N4SwljhwMYTiDLwgmCIrbSHY52tc9z0A1KJNL0+zLJVxLGbQi4X30wLTVJly4fkyMhflq8eZx/NiyyQYmHgYBvpu4NWbG169uuF07Li96zgeIsOhZzh2pJjoDonYJSQmJPmI5ZR8jNXqH7YwWHfBtXMaQgxIF1G110Mqh2WgeLWknCdkgaUaI7BFQoiSukiU3o29s4XNllrFZKWkID6kkBY5WS6K2iDH1eBaeRMx6jItAm4xNR7q1q2pxqOxPgk1RAvZG/NPjCKbdECkt3vnpdZxLjydJ8NgpDewLggSrXKgIfol26HyLRTfDfJYnchabttC8LUu3nj0wiqOmqu15c45r9jSetPQ/T9okmrzkhGFeOg4DoNtosn07udyJuf5p0L+/fFNxz/9O8Bf/MCv/gi68dthducor5NCSimM09WMtDtxGA70M3TdSFeFQy9UKsNhYBh6N0oxvruo3WA32CVbLVOC0169pGbvCWARBfgMMkfmS16otZCCQE32fAdPsmu3A6252Hk2su7UpRpAd71mShUWn382TsplUi7jzGdfPjPNmXfnheex0PWJw43RVW8fOm5vIm8+uuP1GzP2m1Ni6AP90HE4DcQY6Q49setA0trsIl2/iqmvNAufl2feyXJLCZbThhTXSTDDsScG86YinmLlDKKEXFFdaIITgpK6gdgNzkswo58XZSmGEfQpGdDURmcpLsfsNNtqo5qj1+CCg6ib2MeW+7du49Ydpuja4yAS6FNv7+Vcea1QqpVPY0wwdDZY46yUvHCZC6WOHIbE0PeOKdg63ItAGrnGr6Ns61ZxMC3sjLwBQe6pWpkttHMXvytqvfajdzU2tie+sbW83lIbr0YA87RQl8KhM+UmCYHkacTz9cKyTH98Y/8P7PAd3rTnCjmLGTl4LZJ1cVVvDW2hX62VsiweMqnrlbVNowFxDrB4aU7aYDKXTxYf29ymhbQPtZbj2rCJFk6tN3L7/iXQ4qGZj6/K/nV2iaZpzkzTwjRlQ+W9saTNSRu6RNdHDoeO47HjcOgY+kTvbayxM+mm0Dj7voFpqwk6Wryei3uEFRxb5aN3t2C9vjalJ/u453a9W0uvLTx7BK9Ty+p1t6NNXQli+bkX6dhy7bpeqy1wtXtd1MLRLbnSzZuqdcKZJ7WeCPH7Zs7QSD4W3FjDDMUrAV7+a80i9sPqKYmNYwp5A4pphox7Ylkd93rzDbTbUWOVdfPf4D67Hu+bnyIU1bVpa93X2t1ZJ9HufijYWg0CIa7v3SLWlAJdl96vGL44fqnGXtUUYed5Zp4XmgbXMPSkEJgrNqxxmrheL1ynzJyDNUdMVxsDpaA5M6TOJI1CJDmiH32Kaep6Uj8gyfXTa0WkIBpIImiNrqzSPLs3rCRH3cG1LeyuRwdaTHrJvi6Ous+TlZDGqXAdK/NSeHy2Fs93j1een0fGOfP4bABY6Afubg4cTwNv3tzSDx2ffHzk4b7no9cnXr264TAk+mNH10VCF4m95efaJ4o3DVmvakCTb2pAqzzQRl5XeJFAYrLey3glTxNP50eWcWK+TkzXySsHI9mn36bozShV1kW5IdfW6tq5WEVE6Mg2w61F29VwjJa3mgeV9fPm7NTddYMWn7UpFC2wjAbuebhv1ZpowKgP84yh4/b2QFVhWSzSyot9H4NwlJORi8Yz13Gk1EJ/turG8VDIQ28gn59racUFR7xp60Aaj947NGuFousYKBGI4iVE3cqRVaxwNi/K03ni+WJkMaSVzayLcN/T0ZzZMJwY+kDqOrJaua3vIhKFm/sTpEr60SqZ81PHL92z2wz2snrIvu8QOfi4Xl2phGaAmVojSkRLsVqxe9UY4rozrx57fcSNd79OSrW/Cw1591DJwsMNfANWT9S2d8vDGt9901qzzjs1UC4ruRgiP05WP79eZy5X68e3KTjKYRD6LjH0iePB2HA3x4Gb02DsuL6j66OJU/TJuqJSRCSgoXn28MKz+4dkY5wpTbVBd4Zu51Zt3l4TrcjL+jAQq9Bkw9pIuLgPrT28aTX34NcyKCb8vBJV/Pr55ukJr/2Vh6KlGpBpDWq6RtLBo4J2PxrWA4657IQsUuxI3u2nDSitmDKPCJFIqJF5NsELKWKpCpBSIXaFKOATqFcocLtkDSxrZ9F8sG4z2pCVHfjyb9dl752chSVXr+bJi9Kb4USsOAca1nFeSFgjI5x41HXRuBZ/0vrZ21FqZRwnrsmaMkKMNB06EJZp5jLOTKNNqBRhbXgo1XZz9R0zBgvPlmVx5HxYw7bYNbS6GQI0XXAJmwGvdtCetjaY2HNX417FFNsmYGFtrebJl9kM/HJduI4zb9+dmefM+bowzia9dXt7SwjBiTIHjseOVw9Gg31z13F303EzpK1zcQUXfYBCCFYWlLj+e1t6bHHnWqdmBY10F1rGruN4e0PpO2SZKIeesb8ypWgSxiIsudClRN8VLxvZ+WZvZ7Uym71maZuoQNLg4bb7K7GNSjGuhT1XKItHTwXfQSx/Fg1sFmBRijXw2IDHJNHOWNoWpkBB1chWEsXZjt6zq5gZBggpmNy2wGWamZYFjRXplITQ9cEBd90AORxk3MXurWOuhS+tIWmt17fP3oC5AovCNFcu18x1zNRq54ur54qIC4rYdV6KbcqPzzNdCpwOiVo7YhSy2pSdeZlY8uj6Ah8+frlhfC2M48g1WotlLz3WwGEZzzzNPD+dGScbyRxE7QZLgiUzZgvdgiRSjOaZlrlxCtcwPnbWPruVdcQ1i3wBgTd0eFi5Q1KbYACt1bTuH+z6vW2xzpM18FyvNqXz+TLx1VfP5t2LsFRhGHpe393Rdx0fvz7wcDcwDJG7+56uD7y677m57RkOafPO7bOFACE6BpEQeW9oIw0faoDRDqizGJimw6RYs0o6HtA8c9BMnSauXeIaw9otuOTC3G8YQ/FceFmqeyZrvbUNwMqpJirGOvnUpmzbUAhFIGfrxqvqtfoVGUCbWi3iOoB4aGx4TBfiavCt2WcbCV+puqzXKgQxpl20KKORekInxK6jlsJ5Gu06dUrsTSDkSE8I4nPfLTQJ77vpXRojWt3YTYTFuxEA9bzf042qRvueK+frzGWslDIgkhAX2MAB1EacyaVNN54Joiy5RzEtvbmY0GbRkVLHP8EAHWAeU9d8PTjHXWobSmB1rRCi1VrVmwcaxbCBFytQ4wt8h+66vbzwaM1T2LcvQ999ChBbzbq1tdLaO9tOzxrSWXhWXUQjMy0WvpfaSCCRPhr6exh6+r4BcMEfQtcF+hToUiBF4zu38qRVLayUtW5KDQ6StlmtSSZr8kgLWBycjAHpkz21tbRmtWYK964Wirr0lw9ZELUyTxRjEhqKXx1dDh5l2d9pFbSx9JqHlu2TBRUbbNGMgZYWsC70tXmksjsPwWSrTX1WXb4aiV5siQ6KCS0a23YL8/7G0zDRDgmKaufgoYGoSmRaMlVtwozV2ndBxu4Kr+G8NEo1NGJM05kHCME2tBQqHZXjELi/PRFTZnkW8mwcuP15K9I+tkUYyoZ/7CTKG4tvjVx/xvEnwNjt5Lq+43g8ECSYAKKDLiVnUPOGocB0yczT1cAxlxiSaDO9jBCiEMyrd31PTGnjM+9hzwZe+Vw39fBYAnR9j6bIcDhwOBxQVZuW6ptMzq3BxVF+AKz2PufMOC88n6+8fffMOBlDsFTl5ubI8XjL8Tjw8et7+j5ydwM3R2UYIvc3ka4P3NxETidD4PvO2Gd9ZxGKxIS0MhuRpr9H6F7k6aaBV8w4vFOwdeyJGsgXa6W+PZMfn9B5IT8XdKnUUWEJxCqc+oh2GKHGFXbKYguvZBupbCCYBQxLUXKB+Zp5fBqpWZE0rO3DLeTuJBIlmYH7dArxCTbVqy8rfgKbcRLQ0lFKQoM32YhNTg2xskb+uo0FVyoS/J5REBW6A4TU2/nMB2uSmUYuX15XUYy+C9zddZy6tBqcEXdYmfoNgWgyf7VUuz5AzaalLxFStKGUt4fIgcJ3Px2Y8/d4fJ75//39z7hez8RwIHYHrKHIJrpG3/g8h7Rtqzo9VsXO1/n9SfZ04p8+funGLu6VWzeVtSFu7X/Ng8YQPQOyGnib0U7zb9K8HGvIJ21sJzuP3r7ZhWS6fZA1IlDBylwpWd25/bnn6tuLyIvXsVq7yWPN87ICcQApJQ7DwGH17JGhK3Sp0iUxz56s2SYlE6oIYetmCutnbJzSFuIaWOXhy7afqf9PtuvQ8sfWZglCnYrp1y9G/a1ZUddniz69xLy9scWCC1cYCOckw4qx6ByEy4gNfszVtWv8CjWMJDSQbXs0PkSpxZl5eGejh7Ut9y2BosG9m6+fJEiwYZAbP7KtH/UqpN9H8ZHRYtJP4g0w0zgxzVaVmWeAQKlx9RHb1105dvWqDgs4WIiaUWoIXiI0zCmFgkjkdAg83J9AIikK1IJE5z8QrKHK19s+ItqW8YsOAsMJwtfz43+pxt5YVql36mfXUUtlnjbZ4pVR6eu12a89v0ck0HW9UW0lkOfZJZtseOR1vLIU43RXjS8XPVAbCuoRcEAM+FI1nnnX+bjesIVOO0OzBWDtoCJWOjJxzIVxnoDI3e0dIURe3d9xf3Oi6yJDLCSp9L0wHITDMXK8Hei6SH/sSH10xVDDDPJsenMhQOy8r9zjXokLsbM8tREwasnkbIo00Xnz6mKbrbaOKs8/+Irn3/uCOs8s5yd0WajFHrZ3+Hu1xa4eopuj8fRfTC21ig2SmAtlsurJkitaRpDZQ1C/3q7zv8a/YFUGFxJti7hJhMUUqb05gut5Js+LSWj33trbmwGHFAidNa9IMN31ZRltEIbgDoV146giFGTFN6gVwVKoLY3abUnN8NqG6umCUWBbzVzXa+YBIEhAg71fRRjnwtuniXdPC+Os5BqI6uIaBJp8QuslEKpHc42qa45lnhckVFKcSGleQ/oPHb9cYw9C6ryDy3XPsxZKnq3mmusKaAZY8xkjESQOw5EgkZh6YkiIwni9YjvzzPlcuI4jS84uLb0rS4hYHlS9U05wAYY2iUOIXQ+pBwptXLB6q6K2vMnliQwfyN5nb6Ic0zTT9wfu72/pu4HXt3fc3ZyIUklpIQal75J1th3SZuyHROx9nHEyBtp0NY59DKauKiLrHLsYA3SLp+yGUZQ8s8wTiNAfbJRvqYVamqKOiVs+/+AtP/ndLyjzzHJ5ppbFvJAvqhYdxRhdWmotLO3uZHCtf2CulNEGUubF+vNzXVxyawPjmmHTNk8R69aTgMRISJaWNMHN2EEtiZwrX30+cb1APwwcDomYoDsEQhK6IdIfjDs+HJwXoNn17rYoqVV8kJ03VOO/C7JeZ8ssNk7bPkxeXYYIm5bcLltsWI7IZvBuvuNSefs08vhsEuGlBqQmhG6LPBSCVsTTsY2/3/L16mzOTN/PwD8Guux/UIfgwJPP5I4x+Nwxdt5cNqICRoywHdd+aHndOhDXe6jxuWGmbbZ7QzYv1W4EqyJFAzg+2KwrwcNnA18s3I/gMsrtFaua1FBLDVqpKCUL11IAMQI3ipJnYR5NCni8LJS+Ugl0FVInhNChqjy+u3B5zra5NdAwWzoTY7DcPhiTKgrksrAsZuxd3/s4Jf+Uu6rC5fHKeJkoiw1vrCXTtPFt83DBzVCJseW9HpR7EwcSCFJQhOt1ZpycKZgzudj5qAg1rCM58ZVs34ftZwZEmW6e4mP0FGINTsJSns6Z87nQz5VpsTLaUGz0c18KSw2ECHPOSKiM05Vpmk15JwZCchAXHGQMqzNpNfYUA5179dAW5Ar+trjDw0EnCGlLK1t60v54jVQsiiiuvjt5Y5SdY1hD8y01ZRfLt/XbAhDrT9DdhKKvq7HDL9vYg0lR9X3PMNijjWtCrIRh0z8wFRWFLgnHweaKaTXChxYFMU32rrepKEPfc+gjXew8HgQwppnq1pBI65pKgdhFwwJaNwtsOX6IEBMURUMlSKTvj4QQqUws2TrzbBabzXEz44schs4efWBIOMg3U3Pl+e3M5QmGY888VVKXON4u9IeOw/HAw6uBnAt//9/7ET/4g6/Wa6dVWeaRkhf6FDj0iRiF0yGRUgRdoNpnil6CirEjpcHzf5PnOn955vnzZ5s3N0+Ok1gbcYu2BVYdu4YRKLD4pBrbFQxsm51MNObC2+tMUeiOA93QGejU7Dta7VskWvsxzYvXdfZdrTDPNr4pxkpMwjhXfu+Hj3z5ONF1PX13NI3BOxuXNBwDx2NApIBcgAWYQWYjKMVXROndYM2Ld8EAscEt/dgFbvrI0EeGaJunpWy1feMLWIzj4JtB2+CDT2IN0dhtVSzdqSIsGlg0cB4rX70bebpkxgWKRqLa+LIALjEmaw8BojZFx7GHnAsiBZUCYv0BKfU0mvmHjj8Rnn31wq0uKhuvOATW1kxBVx65+u4IrIBI8+xBWMtUhuoXn0iy3aimDLLmXqHRNl26qQExHkauFE4PPdtNNcGN6H8v7VcOQAUvm9mNCx4StlnvqpW8YCwLhDQsxK5CiNQqCIX5aPLTj28vfPGTJzYefmWZr2bsXeTUR2IUxlNPn3wgoC5+TcxTpNSTugMigRg6RALjZTJhxlJ9OmsTpvDJrjZLg6hlHVTY5JtmF9tAAioZFSFXA9WmUllKpeBstLgHE9kmzAZs9DSCVDEq7grQmqFnnxdQquE553HmeZxIi9J3tqFqFPq+kjVgoz4zqldUZ2IqxJi9YWrbxFsHYAvu4vpovePea9E+tnv2NagX3LPjq3NLM/dhd9sI1I05V1iKEbDmpTjuEdbXbaBjs4MtD2/t2Lbmt7ZY/zj7lOQDxy/V2GMMnI4nbk839KkzUEyEfuiRELiWAtlljKrVYw8Eok8Emb0EZMSXhGqkVhebUOEywW//3k/4m//3v8Orhxv+o//MP8GvfvcTug76wZHdYDcvpI7ueLBFP442olgL03w1QzkeSEdBLuMarimFUtX6y7sb0hD5tfwpl+tI33d00W7weH1kGgNJXpFSJGBkFtQYhPO8cBkXfvLlGQmB+4cHTjc3xHSlGx6Zpsy/++/+Pr//+z/ZgMog3JwM0VeFFCEhLHVB1IQJU9eveWoQYR4zl3fvEAJdHCw6SR1vPn2g5MLT8zPLsiCxtxJYrSzjTCmVeVyo18WHaVp9aymVparlq64RMNdKVkX6xOnNHZIih5sD3aFHcfqtVnKxqkrfD5xOt0gIlGzg37Io8+RDe54K02zo+OVauMyFs8AlCdbiNhFK4ILSBUO5b8aEsFD1CVi4vUnc33WIdAQSwZV3xRBIGps8dJHu1HE4JoYu0qfoMlCO7evetGDFLwSM2662kUpyDCKsKaKGSFHh+aycp4m3jxPvnkYj1WhHiJ2DvOYUYrQNx/CMZFFFNXKZ+35zfr6h1FyYxq3y86Hjl2rsIUROhyOn44nkoochCP3QmZ7aNCJBrYfX+wQlRBLRp8MYoyulSAjbqajCOGemufJ73/+SH/3wJ7x5dcuvfPoRr+9fcTpFDp2RSozZpTZGejiY9FK26RQGtI3EmDicboipt/ryKhttuW3XD5aKHBMhKtNk+m5aZs7nmR/9+ImcleNh4HA60UXh1HUIytVVZi/XmS++vKAqvPlIuL0VimaWPDNOM//+v/99vv/Dz814o1UjvvOdj3i4v0Gk0hULE/tqQg9d7EiHgRAsTA0ijNeZp6cnRIU+HokhcfjoNa8/umfOCzMzOkEcOmLfk+fMrJCnzLzMzOcZUSFWc8tZldYXV1y6YaqFRStDn3j1cEs69Bxuerqhg52xX8cz8zxxOPU8vLJqRcmmurLMMI7m0Rcyei1MZeZ5HrnMhQtwjeJVj0xAGJdCInI7ReYpAhnVMzCT4i33d0eMxpOIzu5vGFrLlGMX6EPHMESGLlqve/BM+oM21HJ2ASzCQSIhOvPRCvIQEho6SoHzdeTdOfPuaebpeWKclcpAiL1HiLj2XgMTPfVc+Q1O26Qp/jgFutik2zVy+cDxSzX267zwu5+/5Tov/Mqbe771cEumsAQLCWOwsCoFSG70DSjRoMSgXm/PVg5iq4O3WWvsdMGsjXYxDraf+ope6i5caqFmC8fwElGL0YNYK6ZvQE33rBE/UvE6uQNCKVodt/XsB9nYVu3mGv3UJsI8P4/U2lG0sBRTsZmKUoM1wxxPVqd//clHvH5zx3EI3N3YAjkerLHvdOq5vT062cKZ2hK4TguigWN3oosdp4cbhrsjMXfclIVuWehvb+lubylL4fjuTJ4Wnoe3nMNbNFfK1BRdhdiAqGRDNg/YqOR06ulOPbGP9D6Pzm6gtymHTExwujlwe2fYxzTZDPbQRUIfyRkWKulQyXIlXg3I1HiliJGoDJoyDbxApagBYEHUS7KB4/HI6XjkeOjdMTgg19ZFMeXZGJTYu5Gv934zdGuAajVu8TJka9dtBb1dKO5rCAKqiVor41R5viyMU/GU57225BVgaj3u1QDCIDbgorZSoAGFUVrq6/z6rzm+iZT0n8WGQbTjN4H/MfC/4Y80JGI7fvJ44a//nd/iZuj5L/+z/zR/5jvfYpkXyuwC+DEwRLtxqkpRWLRSUBaUmkxiaMkjpU7O4GrgpbPMHFmNQcjzzHS9MPRHVPv1ZpVWzAfboF38P2ARgwRvNvGe+BDsBgXPvUOC2FsJqR+M1z0MkcOQKLkaeCaVoRO6CF002xCB1AfSYl3f5/PINBWezhDis+ueWd/18wL1eOL46o5f+e4n3N6e+Cf/qd/g29/5iNMB7u6EECowApmb2xP3r+6MiFPsc372B58RTgcCgVfHe4au53Bz5Hh3pFbleH2glMrdr3yPu+/+qtFdHy/UaeGHv/Xb/Ogf/COmy8jbn3xlNf+uQ5INrzje3xNTgi6hMbLIwiVd0aDcP9xyc3OyvDiYdzqfO+bxyt3dPZ9+8gkSAu8er1zHBcKAxBuqRu6vkXkJpB+94618xnweqU8j82isxCIG5mdvQF1UmUtl6IWHV/ccD4FPP77n2996oI+B0xDpooXuUZSsC+flSsmZw23i9saUirskDsz5jtIAyqBUDe5zAsvim4HLUxuAZsaoYko9VRNZB6al8MXbmR989swXbyemGZYSIG2gdOuzM6EQIYrSmb6V6e+rVRoClSgmEBIdQTSBkp+dtX8TDbrfAv48gIhE4PvAX8NEJ/9IQyLaMZfCT54uPF5nLvNClEDxOvEaBXk5JPo5tAF4DVBZO4+UVQNOESQYOaIBY1YhaZJSW2dQm6W2CQbYhW2c8+2xO8LqUjySc1HAwArUhRaKRRMJrGUDeyRsPdnRAcfg3r1WJU+LCxOqhcpq9kqMxKHncHPD6e6Gu9cPvProNccj3N+BSKXUM6oLN3cnbtzYNVukc3y8MNyeiAROtzcM3UB/7OmOg7XbRutLOL1+4PbjN9YWejhRp5nnn3zJ4/0XhBg4P5/RIKRhIHQ9/XDg5uHW6Lxdh6TEqCNzWVCp9IeO4di/MPZSeoTC4dBzPA2IRx1LqUjqiN1AJVJCR8yR/jQRhg6Zs5FTaB5WWz/TFngFw4OsyhM5HAYOw0AKLsW8ims4ul1dNUdM3jrGjaNuUaHf6KDb2hDnvldWz746592SaSW3qjZ/cJoqlzEzz9V5Gy0CWFfkbqG1Ji37cVPNXUuBWCdhFNsE9GuQePj5w/h/DviHqvqP/qhDIj58KPM8cj4/kXO2dj3Pi4Oj6xHXF6vOZFPokoklKt77LHWV+Ok6000fOjgNgeOhp5TMOF6Yp0jNVhqzyS3FjDS2kT4bccRlzN3aqjeHRKpAViuxWZdSdaOvVpNO1mPcd4Whi0St9NHSkS4Kw8EaNypH0sHysu9cKtfrwmdfnHn7dKZgZZqKQIoMfeLm9sTrj17z8OqOb3/32/zKr3+b1C30wwxSKLWj6szh5kS6v7OFaRKxnN488OY7IzEkXr36mGE4gFQ0FFvH2cQj0+tbuD1Y+TEJLD23v/aab/EtLuczem+kpdPtPcfTHf1w4PbVK2Ly8hqBp+mJ8pgpWnj9yWtePdybmu0yU0tBQqEbAnf3dzy8uQcCz9PCdckmjz30VBKJnpojmiJjLYy1MGcv+TXCVYBDFzlE4dPXt3znozuGLvD6IXLoA6/uDxyOyby5Fr+zziWgILIgkkn9YLhLEGJyg67qbaOKZi9HJiM85bLReddSuPNAEEstqlo58mlSnq6Vz7+a+OzzC48XtRZhwuq0bKQRK0tPcCwpOVtEw1pjt/4RQTq8QtS2jT+GZ3/v+K8B/3v//o80JOJDh9VsZ65XU4ldltkYb36yQa0cIirENszB5xaW4B1p3n0VfJpo5wMQD33gdLBat9bCNE3k5WAUWDZjD97UQvW+LUvOrANPHAOQrTvPajcOmIgbejN4H0uUukDXBYYUiSoWPkqli4G+j7agotDlhEjiOgqX88wXTxemPLJoZFJLR/qho+8Tx9OR+1f3PLx54KNvfcwn3/kUwojGM5DJNVJ1pj+dSLe3dnGnBXLh+OqO+3EhpY6Hjz+lP5yYlyvzcnGuuy3S9HADx8H+tgtIKRy/80BIF47PA/NwZZ5mXr35hPv7N3TDgbv718SYbGRVVvrnjuf0SC4LDx/f8eb1K/I8M57PPuJpIXVwc3/i7uEWVaF/+0i4CKFLpN6MPaoBV5ois1bmag05xXkXFgEGhkE4dpE3r09873sf0afA7VHpo3I6Jg6Dae2FXGzqTRPOpADZjD1Bv7YV21FWDMj4B2BVDhuUoVbrVt3Cd/EWV5GWPTFnOF+V57MJjH7x1ciUI1WTo+0YvVfMYeFfLfLDjd3rlGrThrI3iEk17r0d/5g8uyvL/gvAX/4pY/05h0T81OHIds6LT2zNPsvK6+XO1LKLzlrrDa4AGgJEhRIMsDB6pxl7jFude1VjaRNhEetB1j200gI1Bz1a6+jus7aobgNjvelip/EWos8PT7Yz4xUFafBOUKcLG030VA+8+Shxusl8+Twyq3AeM188zhQtaJ5RKSzXC89P7+g6mKbRbnoqFmIKhK6zNlhvTW2lWFUhpMThdCKkRDgc4NAjwcYmW23XRTFSXBFf03ur1v99SMTa0d8OSC8MdweGh6OROQYrM1mfvRIPkeE0EEskdRGJdp2a7n/jKYCV8FrfgWWKVnOu1aboXOeF8/nC8/OZy3mEWugCpBBIITKkwMPtwM2QuLnp6DuhN/jgPcqrrmBWzdnGd9XsYbuVdCV6bbvhcg7MbgNGwBxLa8YqtKdJ9JRRGn+9zVWvPF9mni4L06wsxUDEraEJv9a+9vytGoO0pbRtTVIj0qftvaqLsLS0/2ccP49n/y8Af0dVf+z//mMPidgfOc+M44VSlXEy8EUlkVJHzdbAUaq6QKAioaNLHQZmZGxmulCSgRSH3jTV+yR0neXPeVm4Xq+M45FpXkgproYeBKIT56K0UVFGpAnS5KZbrdVonRINkUVMMKFS0VDRoHRd4HTskAqnY0+OlS4KARNNjKESI6TBJrjcPgx8+it3LIvS393x0Wdv+cGPvuTd3/1HlsOPE3lSnr+s/PD34Xp+xdu3v8ll/BjpCyFaWnI8nej6Jipu7sZSH6U/nug/OUDqiK8eoB8IYyJdbdeKw2D89Ng7+05BMsRKPAmd9tRj5YY7Ss7cf/yahzdvLLysJrwgBUIR+jTwoA+UWhhuBkigUVl0oVjvJqkfrEIwzlQVcg0QelQ6ao3kLLx998y755kf/fhzfviDH3O5LoScuUuBw9BzOvacho5f+9Yd96eeV7c9dzdKinAajH8wJCUG67xLwTz8dcmM0wW00PXGKOwGm7Cjqrbm3FU3jTwzTuMV5GJz441x2Mq/kRDUe9cboQYu48IPPht5d154+5y5ziZVLV6is16j6vm34QmG96itEcd4Oi/NaQrUwTZkrdcVb4ghvvBLfxxj/6+zhfAAf50/5pCI/aGtpbUpwgBtRxWRLZTyMqPJrnkDhWyAShOjaQMiW4kLdPXsbTZ6rWpELpHVrwvbbtpeu13B1i7pX3bASivveSFIWLn+yR8aN451Uz6xkM86tWJK9P2BUoX7hxuuLkrZdZG8WO08+Hy58XJhPHRcLxculwupKqlTIsHHN7UizObZTU03EvqEpAQpmThlNBqwBPP81nfuTMJ9GSgIkkzwMh06pJinD71FEGXRjXoMq+yTVMdCgotGFdO8a0FQra0nXte59OIsw7wY6ehyHrleR8ZxYpkXAibwcegCpyFxOiRujh03p47DEIxgFJUUmldvEVW71/gmaMM4Qutsa6id4zQv+Cmy9U6s/QXaro9tBCE0STXLn5t0dK6F67RwHRefGGS1+ZUl954nD2tY39ZhW1NbV6MKrOOxqR6Ffr2NfdP57DfAfw747+1+/Ff4Yw+J2L2HgyKBwBBc+D4HlmJh0HgdjTYpthhF8f5unyDjZTSvUpCi9YYHrLa+zIXL9crTOXB7OTGOM32XOA5plTfCabcNWbcmnbSG8yKyju5Zw3kMM8jFZK1DFJJGhqHjeBygCId+JmrGZqe79joJglqb5sFCyP5o5Zxf+dVX3L++YRgSb7985HK+kq/P1GWiBOX81efk6Zn/z7/1b/GjH/4+H337Fd/909+mGxKHG2uPvbu95dWrV764s9dlnbggwdQmVI0pWMW8czGjiMnyThuDtKA1W5qSEkLP4fbWZKZjZFwmwziC6cFJsJHPwdtgaxFEe4IcycvE27cj8zRbD31Wbm8EqfdUFT7/8YWvvnpGZUTlyjhlfusf/pDPvnjkh599xfndI6Lwyd0Dp37g9vbAw/2JwxD59kcHbo6JPlWGtBAE+mStoik0Xr94iy+UupDLYp7zYE00RFjKQuP+W9XNErQg6iUuazKqOVuUt5aNAoTga8EGltRgkcp1XvjRTx55PBemRQjpaOm3YP0BYasgdKmF51ZDNs3DTCDQpYGuC9aZp9VELEoPPp99nXDzM45vOiTiDHz03s++4I85JGJ/SICQDITo3NhztZpTdXZQzgVJTkPUzZtHid4rXNYd3G4y3lhhrZbTNHEdI+M4M80LAhz75K+jlvvgHlesbTXGuCLzft7GsW85ltjPcjG1gSCW93VdYhh66qL0XbQGGlVUTYUHySDWupn6QOoC/cE2vY+7W169jtRc+MHvveb8NDA+KfMVnseRnzw+Ml6e+Ad/T/jhj77Pr/+ZX+Vwa+Wt/tn05fk08PDwxgUNHK1tOWIQbyer1Fwp1SIkM3asX6h54pqttx0gmkB0fzwZKCrCkmdjNbrQxvqfE0C0gpAI0lNK4Pl5ZryM5DFT5kpZBk4Hw2LefTXx5f+/vTeLlTTb8rt+a+/9fRFxhhxq5A6+7sEDtBphG8uyZT9AG4RpWfDCA4MAIXhDwlhIyC0eDBIvSIjhARkhLIQQosGNsa1GjI3faDe4u+2mB9/bd741ZmVl5hki4hv23ouHtfYXcfJW3ZvdVTcr69bZpag8EedExDfstfda/7XW//9wS6kDue7ZDxPf/sYbvPPgERfXA8P1jr5L3F0FXj5fc+fOhvsvnbDqIy/d7VmvAsKMaCYIdNFkqQ0BcHQd3NgLpWZCjKQ+WugTrZHJrpfF23r0sLJsIybJZbI54aWxxuRhxtnAZWP/TYxz5dGTHVe7wlRWSOxRqUBecJ8QW1FWxBphrTehGTzB8Ic+Ref3awQZCXWGoKYQ/mHjE2eqaaPxrBkjCg4qHQQkqoNqXcJpo8V3VwNdEoESxVZw98aCWGqklEyWYMa+D2bsw4wglHWF5Mhqc12XC+aIu190oPn5HIxfOLRG2Dmou/HtYdGGt256bXOruEtdpF933iEFEpSuD6QucXa24pWXzjlZJcaVMo89J9s9RBMZKPuRy3nm4cmKN792l27d0a2MvEHHwstnd0ghkIcdmjOpt5y4pIT0phwzXF/y5NEFIUbWZ5Yr3wh0fTL0OtiuL2rAUEVpNbLqkEVMYlVvEpeKsmnIXD3aMo2Z6RrW/cCTx5dcPpkZ94XhemLaz2wvI/urdygF3nzjfZ48vqLU4HLWmf3FnjJkOg3c22xY9R33TzfcP1tzdtJzZ52Mty9Wolgqran3LMQPHuZZY43roVMXcpDQBYKnt4y3HppkFd77L3hmRo8XelmwHRWl4v3sElECUzYZsmGyLsAxV+uziwk0L5pwwqGmJLigh3oxT0WpYlRf+2Em58q6C6x7L/1NPUEiuSp9saanDxsvhrG7cXRd8io4WxlLKS5zbLXZOSvdCtfndtpdKilGoyiuuUmzWemjOBf5NKJFuLrcojlzujnl4nJHnivnm551FwFrF9RmzAJI9RXYL74GXwwO5ZLAUqJrablkHGfOH5djEztstfxGSxSTGfr6pOf0fGNMOMEWl9UmkeKaMt7hD/z455n2I9PuHmXac3G155X3HrPdDXz569/gwfvvs334mCfvPjLAsVMkwvYP/SSvr87oush+f0nOE+d373L35ZeJPybJ/gAAM2hJREFU6xXp/AxZr3l8+Qbf+MpXSF3Hq5/7HOuTE0Tusd50y7U1eNquS1FhmoNV13kWQlZCOlkRYiKXiTxndpcjb379IdurPWiHEhn3M5cXe+ap8OS9K7ZXe2p5Qp7fpOTK1ZMtw3400Y25UqsyziO5FE42G165f4+Tdc/vfe0+L9894eQkcXbeeXy7ByxUit4L2njigse7tVbGaU+eM0qhW3cmgb3uSV0wOq2ciSG5OMUhpw1KybYYN3D2OB9fqjLXghKpoaPWwHZQhnnmyfXMxX5mNyppFQlpZQD0rEt6LbVwIyRAqXOmFsswzbWQs9mBiPDS3RNO1mu6BOebZA1XWLu3ad5/8HgxjJ0GitmsMlfL65aXlk5ddtDDxttgvKW5aAEwGpSCewcC5JyZ5+jk/N72WhrQcgBbwMEOabnY1vd0SLsJtqsfLOHoPDiEGI05pgE3Tb5qae2NJietYrXeDbSLSVitEmena6YYmEOhTJaO2m4HUOhjICjUOTNeD+QUkV4JEeb9SBknE0QYBuZ5ZLVek6fJeNFKIdRCmTPTOKC1MI8jMUbyODJPo4U0WhB1eepxNhLQyRRzLO4UNCquUkyZK3kqzENm3E0M28lTqcI8KdOg5EkZh8qws7baYW+sRLvriWm0tOs81+V6JwK9RDZdYtMbzrJeWWdaFy0Eqw6WBWgsV0ep1GXCeKtsOYBpDQDjwFO4EJuozyEHZRfqKmUJC24AuMs7W4IVp6vSBRBe0rYLWq9HR2efIQ0wwJrDrMTD3i+CzVn7BEKIxHjkaXwa3PjF3LQaUaNXSRkLTCV5/tNO5oDam74bxjcWhc3aObUFKJlaXEkG00evuXJ9PXC9nYDAOM1McyKEQgjFEWUjNbDYDtvRHZ4VMc9CVahYBZ3RF1t2oLl/IRrNVpNWrrky55FcJpQVm83aWj9TBxiaG5Mj4cHSO+uTxOe/eI86V6bdhjyNnD3eIhIZ9iNdTPz4l3ZoDGiyvvqTu2v6VeKLr75OJwIlM+137McdVa2LL61WnM4Dab1Btpe8tOpQhOnxI+bLC4aLhzx825tIemuT3b5/wfbRBUGFTozye3N6zmpzQk6V7dYWtqvrHbvdwKMHTxgfD8zXE9vtzDgURBIiG6RG4rwiFUWKs8ACaX1C7VvDkgEIljY1PCd1gfUqcr6JnJ9EJBZqHkGUGDIiSorRJb8F1UUg2td9pdZMqbODWeYBjKP1WHRdoFtZ2rLUeTHqFHsEwzfAd3bwLJFPYGk27Gw8Aut1IvVrztaJ0wBVKnmemEpAohBXZwhKVmMKqm4JwdtkQ7RmKC0ZkUoKhUBj87Vuv1Kt8CcGW+Q/Fcbehqq6DJHl1RtRQwOMxKmfwdNxBEumqsUrXWenFMRifi2Vkg24G8cZqsU+wziTUvJOs3KohPMbbIyquAaAxatttBBCq62+i9fv6iyiXqQR41Lck4/UYhH1uu3VQjFlQI2TYwhUCv0qcvLyGVqUaRfJ00QMkeF6ZtpsOFmfMU2F/TRzNQyEGLj36h02p2tevnuXiLmh8zQyDXtKzUx5pOt7EOOmk/2esxTJpbLbXpNr4fpSKaJ0XeLO2RkxRB698YDHb71HFzruntwx1dT7kf5uT4lK3W9R4PLimqvtjqtH18zXM2U3M1zs2W4nUtpwcnKCaCCURFTjMEhqMs+hc1krrZSaEYGTTSQlW1iLjqw7YdML65W55bmONiccd4xi5cwgVBq3fCOuxIUl6wGCKdZpB16P4WzCucwO2AZiiKiGBagUaS2LLI5f8y4LeDck9CHSkVh3iVWAEci+2MTQE9MaqJQ8OhuN1+2HyLrrQTrUkXbRinF8mJdRSqFGE+eo3pP/fVipXhxjt642d1k8Px5CJQQlpcSq7yi1ARDH7raCNzjGIGzWK8CAkeb2NPmmWo3dZrcbefj+BdM48flXzjg7XZFSQdzdD3grY+taaQ5aYw9d8DoDdRYOPKe7Ch6ONLTeDFkODzm4jBK8ksyFGW/4oFFArPAnagcJVtOGO/fPmKdC389MU2E1TsZCG4RNn+idGTVE2yXuvnSXTVkbs05y7Tup1DxZJdpqRS4VUSXnwERmphCLwpBBKnGGlXYkTaRs4UPejmzrlVNAR6rC9vKK7fWO8XIPw0CYZrqaWVMJOiPjHlTodUaDUhJ0fcPLzdjbfRJRuhBIQVCxVOWqM6+i+cPWaeYtMUuVZQNZD8Bpk/FKMTkXvRl98DBgAVBdmMSrpR26t8+P8lR84HPBgDSjnyoaKJqoGhknY0na7itTjWRAQkcMnWV5/HNCMPw90Fh71UPPcqRU25iP1LM/mTA7fgKEkOhD+p5b+wtj7KWqu+124DFWUmrouHX71Gra30XNBWehdLY8u7GenKBgE26ciAgpJGN9LdZV9v7ja+b5De7eOeULr9/l/GxNXxWkNC9+qWJsBT2IBaWts85SdAkR0/vOxdI9sTfixUWzbjFyN/hojwbySYjE1KEhoa3vtbmdSaDrAUgriLnnTt/TpRVlquyvR+ahMAwjV9dbQ4s7kAjrTkhJiavE+ee/QFglU3UomZwzFxfXzOPAaVxzdn5OyYVLxAQoszDMnoqcrXW4H5SzuiJqpJ8jIQv7/TVX9apdKFQrjy9tZy/DjFzuSblymiu9WFVaHi2PvamJdRfQlNC+VUIat2Aphall+zpx+r9AcpHLFKLX+YiTlihgIJrlpa0cV7ytTSQRSWiEvl8TQqLoRNXZSmWjVb2hUGdLM0jFFGhLQXM1ADl1FjNjLMOqR1iFKDNQSWRW5BJ4/3Hlejvx8EllnxMTkdivSd1mmbpgLdgSjMxEq4UJZZ5R8cKgaPhOTInkXYPjMFKdkqvL5tGG0PORWlyfy/Cdsuox9U9jnlWSQteZoVYMVDtE+Sw76FJLDJ6fNPcsxuQKm1Z4MM+F3W6k7xLTZDn4GBsw6ACNYju5hwzSvudwyKYd5u+p1ZHaqofF9enjWnjq5HD00mqkb8JJrXWzBtvzrGY7EPpIt+6JyaSVYsyowJxdqz5aI0UMYufvBUAtxmzuLs4hj1Tb2VSJfg9itYftWlbtFiokcbZe7wCsrrCLg1dVK3kYKcNEnQvBvzv5uRcEst3j4ACMXXNZ7o13G1ODVaBFvzQxyPJou7hd10Bj/G0P1QagHrG6LTYgCyBnFFCHKjWrimt/7j6BX4bDp4vjOYd7b2/xijk1SYxSg+m57QrDVCkEKmrX0IkVl1u+AL1+X3hqfi8WcZgmil1HA/5YJMkOcN93jxfD2LGqtHm2bqZpsuqkrl+x3vQHKeSq7HZ7hmEi18o0Z8CaHvre1ECG/d4YQfZ7hnEidT33771EVbi63jPNmd0+c3X1hHGaef/xNXfunHJ+3jlPWnOhfJUlE0LHOhmNU8ZwgNZqqFUp2Y4bCWSpS0agSezGLhBLIM6RVDpiiou7ZqFIssnl7mXFytpLmSmTeTYB2+HYJPqugyp094VahPXVltX7CYq5pUGEGivDo2uqKON775Kl0K8S600PWL6Zqux3l4zDJVQ1VZhakZzpcrZJX81lTlUpXaTOyrDd2YIrgeg78TiNJq29H2Cc6FQ46dZI50CZmoLpOJlR52LxpuXUzcspValaKA42YVGMF51U34EDis2PFAJ932FYCJ7WFAj2ebW1Pzvdcs6FaZ6Y80zXKX0v3p1oZbWqSp7NawsqCx9pF5pe+oHwEW3HbPhOlYQSyZrY5xXDWPnOO5e8/c6OBxeZSSM1uCfn1ZkxiV8Xk3qyUNaksUPnBCdaKGpgYZPmlgghOSuvG/84zVxdNaq0Dx4vjLFXb3KpxcsNFdYxslqvoKUxqueqa0XmmXm2FT0Fa2ktRZmmyVhIp4k8zwuhoaoRFtbR0P7tdgfA1XZgu5/o10JVc4OsarYpiypRBenNnarZj0Zdurm6ck2xXbjW1gDfym0FSQFJ1k0Wu2gVgPguhnfWge8o3j/nK3zBKtVi7IzOuY+kTQcEUu1BI6kPxDxBqSQvONoNOy63O+Yy83h8zFhGNucbzu6dOWhoTRjTMJEvRkQtxSVqoFXM5cjYhViFLgamXCjjSJ4rKZoST8mFshvIpVCnCZkLURKb1BElYtMskAv0we7jNMNclVKEyXfjWcxoA+rpSPVorXUJVmcHKqh3jaWUzAvKVgZ72Pk4pLrsRCieR885k3pLb8bWqRaAbO858NLJ0iR1UzgUmgdxqHXrgETRxFwiwwyPLkbefu+KyzFQNJqeYCM2CTZvVV2RxnsFjuWqQsAxBGOtQax0+0Zo6Oebc2b/IhNOttFuTJ5bW2v0CR5J0Rg+Si5ek25SoyGokQQ4JFqrUfI2F8iKC2wlHoc96uW1q65DVZhzAEl86433ud5NvPbKKReX56w3HS+/dsb6pDP3UIxIcZr3lJLR6jNj4bf2zrga7UiyutKMAXYhBs7OT1itO0u3JNuNhv1AKYXQuwJIivS9serGGJFgnTPq+ndBktFkERaMAleEEYwkklqXRqBOOk7TCbkWZIK5zsTOyDopUCYjB+lqZLO54yCgTeQ8Tsx5BLDwp2UeKhZvdz1FjPO9YSer1JEkmMuvQpK0pOjUy08tBMsW8jigClaY2lLYgu1upRZz37toZctJiL11g3WrZIumKDk3hNzaYyXoct+ba9624+P/5Ea2xIq0SikuN22fsPRItAVEjuiJaO28JteUa2Kskctd5u3He7a7zKOrkeuxMGRQLCWbYqTrknkbegizliP0C2HG3g4gLg09oN7CbOdaqtfQa6X45vNh44UwdoCSK9NUiCHQpZ4QA33X0XUB5sKYR5dwmhApLp0UPMYyyahaBaoh5KtVYtVHcq5sry9td4prTtZrc3+CkEvml3/tO8zzwBc/d5cf/9FXuH//nD/yD/8BXn/9jBBnQrILuR2uEIQurOnixg7a15oQrE1VtZgKixqJRQhWMfXSa3dRhdWTa7bXe3IuXF1egzgwOc6sTtak+/dIIRoQ1PUglj8HQXJcdlmKFVvoXKDMhlqfrmzyaAYtrE9XbMIaUF4q91GtDMPAbr8jz5nt5RXzPHNy9jKv3n3FItGc0VrZ6zX70RcsJ2M08QxIGojrE8v1ZktbpZiI/ZpaKx2JVegIGkhqaUjFgTetVFe0ldTTheQtm7o0cSRgKiaigcBqs1lq11ebjhCFfhWdTjwzjgMhmMpvTAlVFw5RvRHftv9aY4uEQEodKQVTCA7CMM/WCNN2VSyMCNExier16MEXuZAI6QQ0MO6F60l49/2B3/zqu1ztZ958b+LxLrvGXSIG6PvEyaY3BZ5pWjYFO1D7jkMHZ9MmML7DEJ2RKXpHIZVcMlkLzDOi04tv7KrKfi5c7EdWXcdZ6q3G3X4J+AKnBtqlFLxVEmyFNYfb2gztNaOTEqB4HCNGZBAjsZgbpKVa/fV+5Go7cnG5J6bE4BxhqYc+NdCnLpNlYaR1985+1oMb1qR5qk2q4OQVqTMZZgWYDhOohQJHqB2tQstMoJFoOMWGd2UtgJKA+Hdosc8Q578DCyeoSkmFFC3ejyGhQUliNe3BXVL7xkbl0SrE8AlrzbPRU4nVD9G45YL3iweKA3mN4usYajq0dMryXjtD9/D856B42+0xl58327j72hKYT3uuiyvs98iAK5dulkOr6EJO4tf0Jrp1QLUX2EtauO5oPKb/ZyXEyjAq+yFzvZvY7mem2RhkG7zWAMEQArV5HUdVoDdPw1/347X7YZJYTfX4+A2tQet7ePEvhrEXVX7j7ce8e7XnC/fO+VO/74vciwktxQATgdPNBlDW687LXmd2u70rmBg1UAg9KfWoCsOYLSxQqNkWghQ6um7NVIp3PQkSV8RO2e4L33nrEdf7iS++/YQaEvfvrXip3xDFcv4G2glzyQjWbReiLPldy7VnVLPVjlNdCqgHrFmk26yQLlGC1dl3/cqLcQKmhmJotzonmRafBrHzBgqsrAA1amEB0UjoMFduGp1TTxcLEnfPV6sNsT+h1srZ5i41F7ocKLtifdE5Y2KBlvEICOvVigAMu8FVaS2vHRFr/KASg9D3ya5DLnjx2WK8uRRyzVRgvVnj/V5m2CL0YoxwBkYpYRXowwmImJxXjNYRGQ2/aEh5CJaSE/FimWwXp9FHtWIXrZW5mPBi31kbqdFM94gIebZrXMphTgaP5YtaabDhL50X/fRLbL4dhXFW3nx3x4MnE+8+uuKtB1t2Y2Y7J+ZqGI3Jf1udQ4pQ5bDQBwcAS1EDGYMcxe9m2OJbTVX3SrrerlednDJrgQ8/dLwQxq4K71zteedqz1Tgj/1IWW5SycYCsloZoJSSFS2Mo5DzaCi9C0akqKaQQiDPlby0AdoksTriZJOjWquphERMHVOeeXwxoCI8udxxer5nvU6omiaaePss1aqXWoFGEFm6v7SBR65B14p/anJygWi5YkIgqZ14TNHBH3fRvS20+bV27M6cE7y1owkLHm2NInHZ2S1tZ4vFYVh1WOw2ZvzpxKoLL0fKdm/X2pl3a1YnCBG6lIgiTGHAGIGCx+rmUYXGyxcspErBqrnMoL1N1sUukWjnD2g14wvuJQQ/ZVVFYiD0ne1gqaWqOOAk6HL6cQE7W9/BwS0O7pWoZmqdUaxNFKI1T7mwSCk+Txb3A5qUl/VmGPgXHMlTjWhNZA0ME+xH5cnVxPuPdzx6MnBxNTLMlVkiRYxbX6L3QYQG+DWPQxfvsHEmHNfpS8MGaM1Yjjc4JVuVhZbj+9rZC2Hsx8MaQTxllYL3SZtxmudjfdhRhM1qZY0NxaWCpMNy4wdXu3WiIYGcM1Um5lyX8kkJTsMk5pZOOfDg4TWKgTd3753Td4HNysQeLN1mJa/WJecuvlPoWLGNTbyqrRCnWKghhswHgeTHKMFySw2klFpdWdTDgrZg1Png67WZkMzlVi1k76hrXXqlzJSxGPBWTDs9ZEUytqj41joPE/vtzrXeLObL00ieRlIISK4kEabJPCGjbDJ02K67xxFYBmWanT6sKkOZjQbbGVVEFPFkxYzx/yNieIdg8KMDnuLdZK09eClKkoNxPD1v7PocgoLqSrnqiwrN/XV3Gk/NLQ0uiFe2KQVf3J0+uoZAloBKZMyRKSeutpm3HuzZ7QtvPrjmnUd7rvcZ5MSaU0KiqRRHp6tqIhmN1cjGkcsuspxf06Zvf9ECotrwAxSCEb40zsFGofVB41mZav488K/5d/5/wL8CfA74WYzU4peBf1FVp2f5vO/9Xc3N6ug6y4GqFkqZWCoegC4K3ekJ6MLDwDQr+7F6zrIh+4GuM4rjcc7Uec8w4xK5EKKlh1QjWSO7OfKtNx7z8NGWEDteeeUVNuuOLljqS6vJGiOVIhl3E/zYDL1HnJBQm167x4ahI6YOKYoGcZUY2yVVsb5pEWItoNFvrXc+1XkxfMV2gNQZQ0zNlk5EjWbJKJ0Gpu0OqbCiIxJJzCSZMWMwhpPxeuDiySUlZ8ZhNCLOYt5JCkLpEjGINxSZ4U7zaLtwo/WukPNo6bOs5ApjqVxO2cKD1jygQqh50V2oWB14SOJexKE3gLYrtzM2UBr47s6uhpr7XMWEGSrzlJ1Rp6XYAqnrlh3UGIZ1kUyK4rXxFAoTitcthECVSA5WBrudO4ax48HjiS9//TFX24lvvrflvcsBkRUSbYOoqVpRlNcJmBNSqJqd/OPYnbD92ajTbVU/iHi2cmD7y1otPS3OW0eMpJhI0b2PDxnPogjzBeDfAH5CVfci8j9glNI/DfzHqvqzIvKfA/8q8Je+3+d9v9GKWqz3u3HE62LoN/jmgsewvpuDFRWU0sCKBu4Fo0muzXWSBUlX3xIMcDH11L3lStjuJnY7J7k47VHnDmsuk1YjFlh2YtRd6vbcz6it4sEBveAUUYEFCLtxDazixl4XIy80hLmBdocaq6Zp3lz6g7KIuXyKLSKH/DBYF5+iGhjHgXEaja9/mijZ00G1UoOQ1IxgKSCqajp72to+3diL8QPmqt6JZbUCy8bvZ1rbXBR/5bhnwOsSoN0XWA56cXWXD/Tr3do9P9yRtbXjgHBbTCwHoNU/6/jSLa6CuLY8gXZpdmNhu5242k5sdzPbfWaclVx8QQnRQTzbAJpYowFtBwCxnVZdNgtdvrod2mEWHZ214inCIyDy6Bp92HhWNz4BGxGZgRPgbeCngH/ef/9fA/8uH4Oxl5y53l1xFTObklitLM5JvsKuVj191yFi0ky1tsq4iXnObLd7Iz/I0XfvRNetDDXNYdHKagBsVcgqQELpmIvy8PFEYM/5+WPu33nAvTsnnG029KlDtBIooOb2grm5pqdWCGLssgfbUkr1WDd2VhEmLkahEDQSNCwgjUNFVhxheZZjHxVbIcy4rTvMIry+S1Z2pwlEkb5D1mvqXBh3e8pU0FnRyeL6abCagMuray4uLq0Fd2zAXDAefYTLBodJ8B3TXHQrjz20eDbVbEPtWZqawA5Zo7vhDqi1wDWkSOqd8DJEJ6ZsO1qLmQ9GaT82D8fCnOPGIkcs7PXQKKKDA3lG/ini2Rwvp23rTwxqlXQS0LDycuVIlcCUhau9ME6Vb377Ee+8M3BxNfPGuwPjpIx5TQpnIJFSDawsOlFlYrXuWPXrJZuAWgtVCi0UMhJUaIZ+ZLS+oNoUsCPNubDfDQRRkrf2Kg1P+HDbehb5pzdF5D8Evg3sgf8dc9ufqCE2AG8AX/ig9z8Tb/zRMPdrZJrE86AJ1AwlCHQp0vedpYtCZ2QOMtrFLebO5twY3GXpKhM1/nmpnqprOzv4pAxAsp7vwXjXLi4HHj/aImrEC7VaWYsh57oU+cRWwE31nUcdvDJXtXoqLnCzOca+3Kutb6zKjcbYd+xlN6/LrtMAHi+wc6ZdPXTOubBCcU60eZwoU6HsCyVXxmvTfb/e7bjebqlFyaPtzoFEFGPcobSvtPZdxds4mzHCYfs5SrMdQwvq56wB4xCU4508Gkjpz8UZZXAA84Ax2vcdGpOO5ijHM/zw7eL+/UIUsniFOPoPy47eHr4RSKOqETP2DOznyn4sPHyy560Hl2x3ysV1ZS7WlRdkc3R9PKVq7qQzDR/o1Mw2LEZX92TlxqJ+85raTwbWVS8tDwLEYlmDAjV9xJ1dRO4D/zTwo8AT4K8Af+b7va+NZ+WNbyOIWAHFKnF2tuH0bEWKgZWLH6TO2gNLruy2O+vD3u2tC6hU+n5FSlDpUSKqier50GbgVa1FMLvbaQ0Frv5RhVqNzGG7K7z33iUlV95/eIUAp2s43dhHHei+6vLvkq49um9LYw0sN9QUe8RUONWQ2pSsWmxJPguHXZzS4OrFdV1iYd/LUMWkQR1Nd+S863tEhVEn5jFTqAzFJLbm1qMdxGSVFUvl1bh4J81db6eRq9XvH6WJD8cheNihDsBh92xlYFXqG1d6WNz3kKIvYO28g3eu+fVTZdFdQ5fUG8tzPz7BwS+7RpbpYMnTt8uJh12NtmqxMdom0dpUA1djYTdlLq8nvvXmJbt95o13R96/LuY9didIjJTaUZp344tNq4EIEk1CO8YWADpbbXBA1147NObYiRurjklXB1t3fP56KbC35gatMBUj5fiIRTX/GPANVX3PJ+tfBf4kcE9Eku/uX8QEHz/yCFFYrU2W+O69U+7dOycGK8cUYamfn6eZq8tLpjkbY+mYQTrW6w1WXb1CMT2uYfLJ73e7amXOsxl7CeQqzMU0uVAhaI/QcXmZeePNR+y2I1947SXKXHj15RUnq/WS9VqmdiNFaPH00QRqLu7CUX+UaouYG586k2MOIVBC9Tgc9zEdhWxx/DLZferoQY8MlzeyHTkSgpFUxNSRi1J2A7NUdvOecZwo2SZ8cGMPEtEiqGulZ/WGoGrPqypzqcu6Uzk6pLYpuWFWUSQI61VifbKx3a3rbnT/WTjlAY+flni3Ym1ul9zcvQ8G70aFGZjAQk4REFKXzHUWLz1Vw3RUDWcJ6I1jV19EiwpZe7IGHl/ueXgx8uDhFX/nN97gejuxHdcMc09MHWl1B4iUsTLV5k8278JixUCkT7Zp4UQpIqYYVDzT0DyM6NJRreAqZ0tfWD19A3MNO7GMjWV65nkG8qJ1+EHjWYz928AfF5ETzI3/08DfBv4m8M9giPy/zEcUiWhDaBVOeN1yOLiosOSDTYnDthpr6rcUVvVlusV6Dfs4jv+qHt5r7psXavhsM5fVgKZxLOz3M5dXO1Z95PREyGVttcq0dscWJfqtXmrnj3aONpPbDo/HrGLS0OI59LZItHj/5tZ58BBujgOacwOsaQtLMEmm0HK90ar6WmWftNxt8onms1+KQwBe7ONKUBTPEGhzYY6N/XDCnjIT/05uNm/4semHOHs3HPO2CNz4vRuUHAAqO5zlAh96xuXYOb7JEHvzO92Q1Co651K5vB55fLnn4npiP1b2s1E2z1Wotc2AYO76covbfRdXamlhRDB/xz2LG+EDh40gyGERV/c6ZXkuSwgiglcp2iZ1I3b6gPEsMfsvicjPAb+CZWd/FXPL/2fgZ0Xk3/fX/vL3+6xnGRKMHqhbBbreBBBrMUHGWivjmJmnTMnqBTIJiRs2J1bJtN1nSlGGcSRnKBr9AeNUXHjw0KfedRafMgmz37zGN57rwJOrPeNU+fXf+hZnpz3/4Pglzu+c0XfCqvcGBWaiqMemLdaztJyJWTTEWCBXJFiqREJz7xISAjXgMR6ev2fpyTdm24bdH4Clpe96MbpD8KktDRNtSqZVYn2+Jq2StRQPmTJXyvRUzrcIFCcMybYI2s4uzvhqLEC1VW0d5YbbMSxufDBPzUodPASRFoocFkrzru0zWmXZh87dxaB9Z5eDK26nb24voR7qcFVsUWuFLBze08KhilARtvvCN955wvU+89vffp/vvPOEIQcu9j25rtjXnql2hBrJsyJS7TNStGKhYjn6k94kyk7XazYr4/Iby2zpQC9I0mVTM+yi75LfYd+YinlWNVi5t/pvM7Y4dCk6/XQrxpEPumLAs4tE/EXgLz718teBP/Ys7/+dDBFz5WPLjUZ3J0um5sI8zcxzoVZxRF7oQ0clUl3zTdW65ObZa9klLEouuVjRRwuoTHHT5JNtRQ3EaO50nSfGycCT9x5ecH0d+eIXXrGwADs+K4hxwgQPrBbk1DooONor7blz1BlPXXKiyad2s0aOcISAHQz9KGHXVvfD1rV4ByLGYS+GFBKShQsiwmq9Ikokp2Jhg6oXAanFG27sOJ+bVlkKaTQU7x+3yLfduEPMbQz8C5VzDEc7ui47/2LkHLIXNx56+P2ymC0T5allwI28ucO2q5uDb2jmcmWPPuawQLUULATmnLm8GnhyPfPg4RVvvXtBlRU13UclkTWRPfxqoopRDvdAvYCoyS2nlLz1GGaB1iLdTskYd3z39wW6teceF4gZzdphYQ4Ba79e/JYPz7HDC1hB13WJ+/fv8PLLZ3RdYJ4GSrbVsmpddvOclcnS4dZjXYrRD/skFGmyy+K12co0z06M0dwqU5IhCDma+B/4jlW80SD0aC28fzWRdhPffOuCe197l/PzNT/ypXucdj1Bd9a8gS46IssCgCPP4M0cabmxph1WrcEkBEJnJaJFTYXhMJ2PLPnIX9YWfhxN/KVuQKz+WhePw0o2Y2+ts/06Ge3dFMiheHxYvIpPrKlLBfEZYjUGgVB06a61cwzuMh+MHrEwKjtnX0h4JVp1l7wtWw5otd3dPQVd+h3M02kmf1C2Od7Zj5wZsTBhYZ9ZlpOwLDCHVfHg39ufWnNQCMnSqHVEKnSyZhVPyCT2VRyjsFBIYgDvT8j1qK02Wt/DnK2qMuwnVtc7Ugz0KbLpN+SSGecJwTJM7bDyPJsrHyNNNKV18Fnt/MF7AazTU5Sr4V2uhneY8v5DbeuFM/Z+1fPqqy/x+mvnDPtrxsFYUexELR0XpGOSYpphRZmmmXGqxnjSCtVFjCaqqMv1mPzTMGUk9qRkZG3qSHCOSpcMeKrFDB5AwsoIIJ5cUcpEd/KQGnteffUe9197jf7sjnd4FaJWgleEW77Z4q+mwplSMpddLExY3F0tRAmk3tpaa7bMgrbtftnUjidp813bXuVG7ZuZhgNiW4NvJF0gkpBU6WtHmgNzVwhRrJd7ACm61AAIVlAjS8AQrCw5Bi9aCgc3PgTfQM2wSjUhSlWltqrCI4Nrvk7FYmQa2IdYMU4tvrO1Rc8Ki5oRt3GcMmsAV2yz2gGzBQvBU5bfBTI4/hI6JK7pQiToiBShkxPWXWYswm4yJR5SMBHM4JuFsPDDB8EZg5WxWOdbVSVS6fvI5167w52zFfv9QL2aKSqs+kSqwebxMCEirNOJacB7ARQYOE2pVg9gX0EVoYry8OpNvvXoV8h1/FDbeuGMvXnAjYVVbt6TBWgr5SDfXDx9ZnPGLn4TmDD5p+p67Ms3LB+qxVVg1JhrpXJoY/UJaNdYKEXYDZknl3v69Yqr65HNycwq4dS/2Vzh5fPDMmHrUr3XaJI8MpOjM18Muzn9cvT7py5Sux7t5yPsznbLtmPisVGAWg/ZAJEW9PvObO42oohaLf3hP/tSUQ6sMe1mtGMObZd11z2Yg2/RUiPbamHPsct5BKjpMbh1fE5H/7+5Kbf17rsvzNMvN2/AsdPj4pOlY6wIqDJNlf2Q2Q+ZuQjQ+RraWGmaHyc3rv1hUWlPmkdi5b4ilWG6QPbCfhjZTlvLmTtt+pxnpjJZ+JUHp9g+zMWW7YkBQrGFZfaiqiFfG9f99xgvnLFblD2jTIQE3apD5kqeC9ajX6l1Zr/PXF0PlKxkjZQaqGqEAqrKXDLDNDPOym5sHPRG78QSF1XGeSBXq5Ffr1ZOj2UgSqmBnIVaC7N2FIQHjwd209s8fLLjpZdf5r3He770hXO+9IV7wMScH4PORLGactXMNM/YjjaBWGNOlAROIdWELmotjhR7vzlPTR44bGNHL4GTyCyZhmJcbt6IE5Ll8hW1xU2FGr2kP1Q0mMBgf2KtuFrUc/riRS1iTSO1WOl/V5FivzfjE6zSz/8WM+UumueSawHNKNb73RZCPAwJrnNfm4cesAmvukh0K3XJPDZAagm5m0fjh1TLwa23eFwprgnQkG5qsF2zCrlGtApTUaZcePD+yDe+84RHFxPXOZHDuTX0iIF4hQ7FhULK0W1px0ND2yuiha5LnJ32KCPffO9XuRrf8LApH8XlvikUc6nC0Hrtj5KOR8U4x98pwDBf0XonPmy8cMYObQWz3S/EgBRoTl6p1tJq2leFXKxU0PvNgGA3V23nL8VAOSvK8hTXkbGUYhVlIiYlZPty9d1YKTV6ftlKb/dDYZ4nYkw8fHRNTB2vvnwCYkSOxevnm5w0/jmqxaiztBiw4wURchzvVkWlulPe4k6vsT72AMBd4eWCHXYWPcTBjY+stXpylNtGsGYc8ekUrOMLMR03bWQaPpkbgo2qodx+vLZhekjy1C4b/DpbWepRbf+ShrRrZB5M2ydbea4tJFLNW9C26y8A2FO7uHsQTRQCOKTeWuzedniVZae3kmmhamCaYZgquyFzcT3y5HoghzPTbsMWnLazt0xE9RVqydm3BOwiHWZCkykZFnO5f5f3rr7+wRP/BzxeOGM3NN6qnmphWTnbTc65Mk2WA+/6FbEoUw5WAVcq4zy6694IDIJ3PAni9EiKdTFJhS5iIIrg/Gg2w0Ks9LGnX60sBFBTqsFj+t02881vvM3j9y9IMrFKyqpX7p6K02qxGIfxlFmffamKhEoxKh2TNnIe+ep99w1WEgnL79oO0BhrDqP50WLlrUmh5X/dYOy7FFJH3LjOmyoxz4defIWFtSV6/FKN6x1v+DGabDVb950fP65a87Lo2FEJaGvV8H7axdCboXrxyOKbH9R1ni4vOHIazBsCL5Y5/Jl/Ig2dVvWFUxqq4SzYCg1OLRqYSqRkI4h8fDHx1qNHPBi/xqN8TZGeKh1ZYWgOT/MKpMX/BoaKGJdMaRmYmkErOiTyozXKzG569Lsxi49lvJDGbmk3yDfiUXVW0swwViDS92trZNlbQ3vOhf0weTzfDEZMBUSFELrF2IsGalAnMzCUuNbZ0xtGaNl1idRvnGvNapfLDHlWrq9nvvrVN+m7QJTMKgl3z1d0X7rD6UlP62sXIMQeoRyMvXjFmwrJvRerdL3phskiQS3O9ag3/MVDDHswIIvFLZcvITrV9YxqMZGBvkeKgYmareBDF2YU2xVdatzeO2anlzZwSIIQDDhZkIVaFZ3zor93FKl6POwaz/4OvWHs4h6IpTJFhKCytJ0uZ2ZWe4S8+8bwdJguy5XxxactJP7qcokDgoVmU47Ms/L+k4E33r7krat3eWv4Mo/zkxsfvXhSS9nghw298Wy3h0eDLTdVv7er/YMcL5yx2y5RDtxs1TvAluq2JvkkDf+gCQHWJYBiScNEAjU6So8uaR7BXNDkRAkVW52DgK5sAhu7iN243mu6J1XybP0/Odsecnk58e6DK3a7kVWnnGwSXVJ/wNlpJUXoe6FL4mkUQ9tLrY5aY7ns5RwPE3QxjaVyZDlNFjR8iZXDIUev0VJvakh4Sze3zL9V+3m4IcYIi4gZezVMQ7yQRoMJGy6ki61ZBZBS3QPTJc72u4mIS3ZJpKp5H6rtfrg34n2vH0hK0TwUDvFqAxiv9jue7K4X4LP93lhZPQZAD2BkA+ZUEDqgpxTY7QM5w1sXV7y3vebJ/jFznXyR+uhjweo+4fHCGXutlWmcGIfBq+UKNRsVkBUpCX0fTQJ4tt1+HAdTaMUEF2IMJDFEGYTewZ9hauIIlVIslXTSr0wOyN0vgljTRgwMc2E/ZWoN9P0ZtQpPnlwz5wIqZO2oWfjqN654660t65XwykuRVS/0HXRJeOnehn/gD77GnfMVL798wr27a1IBZSYGA8tKzVg+1Yyu61fGd+ZwdguLUbxn3V6ILYV1DNotBRiV4CXFMXVWaFQyeZ6pCFmFrF415sU9p6f3jNnW+1S1VObROc6KPap30NVaqMWIPErJIEYRTVYo9bBjewFPIxApXpxjgoTegOQ/z9nxjaOdUcTy/f6Dnbdnan7jje/wv/zdX2GYD5wpx+6+DT180NHTFjZYOaqFE+NYGL05aDfvPrY5/aKMF8/YVZnnzDjlZbc27zYiOIdXaHXZtpOUUkx1UxJEU1dpfGE2rEY+HLWdmkvopbHRjD270F+/7gkpoDIxl0wN6gwmkW5rpa22CydKFa6uJi6fjHSdst2qKdR0tovvdmf8fa/fBQKnp5V8alabHAdIpbiCjMW4S2rq6bmJ40r+s23ycoizRbzI5ugPpBVkyJKKVHGqZWk7u5XVSox0/Yq+W5m7Xl1dRGUxdtzYxb2pkh3lJpCty8c9gnbkh5ZeoqfzlkL3g3uiyz0yBpbW1QUspBkNXBORJYv2aHvFV95+i/30kQmSPhPjhTP2dx7t+eu/+C1eubPmJ790lx9//QwJkX6dQCOrdQeaGMfM1fXIPGX6JERRYwKdCkigX50SUiIXZZoPqHQDgFBroDk/P2OzOWGcJvbTYOCYFmMUFWXVd9QqTE7JpI0SSJ28Mni/PQkojONAydV3i8Dl5czXvv4WZycdw/4VxuEuJycrXn31Dn0fmWbLPoRoddGGzOvCWxcW1/2puNx+cCNoFYMHMC+GSMBRbC9CiF1PtzZq7a5bU3NGc6bmmRgSq82pU01XZ6CoVtjRnrsiT993aC2U3FHLRMkzXScuyJgtPaosVGC/+JWv85V33gMVGizRiC+0gV7KorzbwEh1//fp/vUmr/WVt99mLh+Pq/1ZGC+gse/4a7/4LU5WiX/pH/0xfuy1E2KEvjOyilU6I8UNu91ArTB440wMSs2ZPBUkBE5ON6w3kWG0GnkcbW6llFqVkAJ3zs+4c+cO290OroxVZl8nSi0Eiax6272zx7BVLZ0nGFeeSO9EBwWYGceZWRTUynEvLie+9rUL+k7RmtFauH//nDt37xipxmyf2/eRsEmuZWbsJSY+0TjcDzru9u8BpRLnQF+eLyCeezYtH2cNAGhRar+xnHsukDMiQkw9jZjD1GYqXUqekPePKoXaJ6iFmju0TuQ8kxKu+Zatd0GtK3feD/zfX/ka/9Pf+rsfeL8/MJR9xvi2auV7yR3djpvjhTN2BaeVqosrZ+OA4Npm1nY5bvzr0P3R274XatrQ3eNqvSPkliM0+LuO8nAsy/ccQODlX4sJq9O63WS+NWT6YIvf/S0fPpFvfO/xa4uhy82/lqd+9r+Ro0Xjuz5X5LvfL3bWSx2AHO7H4aPc1fa3laq3O/ALMESf48ooIu8BW+Dhc/vSH8x4hU//OcAPx3n8MJwDfHzn8XtV9dUP+sVzNXYAEfnbqvpHn+uXfszjh+Ec4IfjPH4YzgGez3l87wbY23E7bscPzbg19ttxOz4j45Mw9v/iE/jOj3v8MJwD/HCcxw/DOcBzOI/nHrPfjttxOz6ZcevG347b8RkZz9XYReTPiMiXReSrIvIXnud3/26HiPweEfmbIvKbIvIbIvLn/PWXROT/EJHf9n/vf9LH+v2GiEQR+VUR+Xl//qMi8kt+P/57MSH5F3qIyD0R+TkR+Xsi8lsi8ic+bfdCRP68z6VfF5H/TkTWz+NePDdjFxP1/s+AfxL4CeCfE5GfeF7f/xFGBv4tVf0J4I8D/7of918AfkFVfz/wC/78RR9/Dvito+f/ASbO+fuAx5g454s+/lPgf1XVvx/4h7Dz+dTcCzkIpf5RVf1JrDTyn+V53ItjWdgf5AP4E8D/dvT8Z4CfeV7f/zGex18H/nHgy8Dn/LXPAV/+pI/t+xz3FzFD+Cng57HitodA+qD78yI+gLvAN3Cs6ej1T829wDQRvwO8hFWw/jzwTzyPe/E83fh2km18qBjkizpE5EeAPwz8EvC6qr7tv3oHeP2TOq5nHP8J8G9zoG94mWcU53yBxo8C7wH/lYcj/6WInPIpuheq+ibQhFLfBi74HQilfpRxC9A94xCRM+B/BP5NVb08/p3acvzCpjVE5M8CD1T1lz/pY/mIIwF/BPhLqvqHsdLrGy77p+Be3OcglPp54JTfgVDqRxnP09jfBH7P0fOPTQzyBz1EpMMM/b9V1b/qL78rIp/z338OePBJHd8zjD8J/FMi8k1Mm++nsNj3nkiTgfhU3I83gDdU9Zf8+c9hxv9puheLUKqqzsANoVT/mx/IvXiexv7/Ar/fUcceAyX+xnP8/t/VEGuv+8vAb6nqf3T0q7+BCVrCxyhs+YMYqvozqvpFVf0R7Lr/X6r6L3AQ54QX/BwAVPUd4Dsi8gf9pT8N/CafonvBkVCqz612Dj/4e/GcwYmfBr4CfA34dz5psOQZj/lPYW7hrwF/xx8/jcW8vwD8NvB/Ai990sf6jOfzjwA/7z//GPD/AF8F/gqw+qSP7xmO/w9hKsK/Bvw14P6n7V4A/x7w94BfB/4bYPU87sVtBd3tuB2fkXEL0N2O2/EZGbfGfjtux2dk3Br77bgdn5Fxa+y343Z8Rsatsd+O2/EZGbfGfjtux2dk3Br77bgdn5Fxa+y343Z8Rsb/D0Nal+Mz1K1GAAAAAElFTkSuQmCC\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "demo = demography[0]\n", + "print(\"Age: \", demo[\"age\"])\n", + "print(\"Gender: \", demo[\"gender\"])\n", + "print(\"Emotion: \", demo[\"dominant_emotion\"])\n", + "plt.imshow(imgs[0][:,:,::-1])" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 25, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Age: 24.706228912787836\n", + "Gender: Man\n", + "Emotion: happy\n" + ] + }, + { + "data": { + "text/plain": "" + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
", + "image/png": "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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "demo = demography[1]\n", + "print(\"Age: \", demo[\"age\"])\n", + "print(\"Gender: \", demo[\"gender\"])\n", + "print(\"Emotion: \", demo[\"dominant_emotion\"])\n", + "plt.imshow(imgs[1][:,:,::-1])" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 26, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Age: 36.036305006492086\n", + "Gender: Man\n", + "Emotion: happy\n" + ] + }, + { + "data": { + "text/plain": "" + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
", + "image/png": "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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "demo = demography[2]\n", + "print(\"Age: \", demo[\"age\"])\n", + "print(\"Gender: \", demo[\"gender\"])\n", + "print(\"Emotion: \", demo[\"dominant_emotion\"])\n", + "plt.imshow(imgs[2][:,:,::-1])" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 27, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Age: 35.126786088918394\n", + "Gender: Man\n", + "Emotion: neutral\n" + ] + }, + { + "data": { + "text/plain": "" + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
", + "image/png": "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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "demo = demography[3]\n", + "print(\"Age: \", demo[\"age\"])\n", + "print(\"Gender: \", demo[\"gender\"])\n", + "print(\"Emotion: \", demo[\"dominant_emotion\"])\n", + "plt.imshow(imgs[3][:,:,::-1])\n" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": 28, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Age: 37.149563607061395\n", + "Gender: Man\n", + "Emotion: fear\n" + ] + }, + { + "data": { + "text/plain": "" + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "text/plain": "
", + "image/png": "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\n" + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "demo = demography[4]\n", + "print(\"Age: \", demo[\"age\"])\n", + "print(\"Gender: \", demo[\"gender\"])\n", + "print(\"Emotion: \", demo[\"dominant_emotion\"])\n", + "plt.imshow(imgs[4][:,:,::-1])\n" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + } + ], + "metadata": { + "kernelspec": { + "name": "python3", + "language": "python", + "display_name": "Python 3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.6" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} \ No newline at end of file diff --git a/test_imgs/.DS_Store b/test_imgs/.DS_Store new file mode 100644 index 0000000000000000000000000000000000000000..5008ddfcf53c02e82d7eee2e57c38e5672ef89f6 GIT binary patch literal 6148 zcmeH~Jr2S!425mzP>H1@V-^m;4Wg<&0T*E43hX&L&p$$qDprKhvt+--jT7}7np#A3 zem<@ulZcFPQ@L2!n>{z**++&mCkOWA81W14cNZlEfg7;MkzE(HCqgga^y>{tEnwC%0;vJ&^%eQ zLs35+`xjp>T0+ZSDa$L#188UffQI@25BGqWtcIMl zmYRkrgN-GZy^EC%gBR}$9tJi~cf0pC3`)uh49aii6d1gO_}HH_xO$p7+IjdgNHB=- z;65w>vH%Dj{ojqcFicfZ0sBYfGPM2+`RmP!lL4m(wf@3 z`i91)=AYd?y?y<#fx)5iiOH$ync2DdwRObC=AW(Yo!z73lhd>Fi_5F)f4I;9(Enhe ze*XvT|Avbgg$o@61B3zohYJne8}$VdV_-7!Vv$IzgUwt?pYnxZlgT7~ukONO;@3DN zH+LJurC=6Vdv^2>+JDIYp8@;u{|VXu57_@7*F1m^LPIqkh!}tXcbd7;zmDi5PagnW zJ5qbU%m=`x=3}uhIz|54_kWONv>jOaN?)d<;+p8a~bVX23 zF*C;ob3NPHyRb9#lE8{SK^$#$N%4x-#Ab!UOg6b^DKLp!CbaIHToDG}OIRH|0BE_}1jo_q;C>UFq--Q> z|G%oop+^FQvCAZ^^z(1Bug_B+fG8Bza`d`dKLi()fMkW=`71pDz2gr+_xfQWbc1>2 zl92TQAe9@XEhq1*>?g#nMLvlkok3q#yJtzgH9o9Ch=#_V{1g43YG`v~hWfXrhh+_8 z#m$hjgMYlLCNWtQ<~jCUDHA;ZgpYZEt>j#b*0;hs!8g(!hjb`W86A&rIhF(|MqCqW z2meQ7C+DhwcpL^I7me9~PSj=Jz5yc$!?f^sxd-64|7nR5>HeRHdpoR?+|*Q+SJnTaaLHo5 zoLhYW!1gD0ehtObGgU}JqQ<17G<*?lrtjp+g!9y$pBQ}ohK1yzh;cL6-HFNl6=SlQIKv@E}W=6!nryzeNCp-1!I?s$^>LNU7lJ`A5bosK0Js#uh97P&;G(!&y zOd@~cC1N5hPw$2wfG}Q2sCG~0|34~OIrlAC1{=m* zNtM_Y_dQuC>?e~D=7P;X7ImcA?EtFEZQBZ`dq!K{Ou;pHQR)M*rh@WokgV_npc3R4 zw25-Jg#YQbyy+4y8pl-sN%$>!t6 z-4@Uj`v4T9$g-oesOgVyFCTyk5@;C2?mwV=wiOcX&wZ?v=$!*XG6S<-Bkr#XU-qG@ zX6%}zp})TP*8%e8Wt-eos!@(B8(?*qaW?ri3xb$O`Q+yyL7!Ln-;~vEF;OOpDuUCk zp={zQ=L_#mm)iG*Buy;rV)nonJW&7p_2qI72_U5k2m6 zPxgcMmZCaj+|*y`Q!et=r2EBetWBUYnpI>QQuDV4dQAH+;e7g1mK{y}4KFj|Ub;~N zdawkl{_CL|#f?lm{C44VL<4g+xlCU~`Q^`V5Ql>>H#W|7c0~!o^FY`GK&-s|9B!T4 z>Jc>Eflv4*$RhhXVi9^o&U06K|0FA819rc5L4PavSlZfelYFD+yx{VEFIt5P{7zU6 z)z>uPNXX%i-=14SIm(!~axbhF11hU`Cv{VyJ#TMCw(eQoj%Mz#p!ZL+AAm<9hX)wn z+@uo>*dKt)Xc5Gsh}Gc-+L^_4vsBLULf^rvg6 zfY+<_=EnH;xoSIODs)j2f#S^lpQY409HC)&nU~RK@f}B8%?|*=6YqZB1RHU){OmJy zQD_U*ToZWwi?)?uNW%lrH5PlBc%Mve-{(OWvRB82Cf1`)Vvh=z=tl%q`7DAIA6p>}C|0Bj^6zwn7Z0N;P3fV>44jv3pbxT#iYvM)0` zXrZHj{)H{IdCpD^lE-@Pp$V5KUr}zFL#UG5x(TtR2eo_cj?@)=SpJENIS)A$?~1lRCPG!5i;4!lqu@MsW1kMX zTar!-?UbXsf5Hk(5`u8dSM5i<&K>}{f1M+TP$swatX;zAnY`+c%k%%JiX)IXs~TTB z8fdr;zbc_n0jGYPzda7-Svy7Bs+wx2fA=z{EvKhgFrXsnqj&Ultz=RtQ9m+KgXydP zs&SFPjXr^2ngro=LFVC|gQ)UhSf281`eil-xbA) z$AeLW{qe!29W8k5})(|V8lX+@r9to?AumI1?V248tc>f1JFT& zvT5i#ESvzkZn_AaX#GzNnJzsl2;20~Lh7jhPnMt<^!(CH?IjXb^)ZSCZFbDi^|Eoz zlV-}ahJ+)L#D zYxG)BeQs08(Wh=p(!2awTIg88zfuTQE3@eCYY6gRoR8rV^W%)9rwU+EyZwmrJG6g{ z4#i`FEfAueF_U*HTl#~E6(2$jj65}{S zLKts$xPB#dyRDDJ1K?MOc1+ur!W@&30^Wd()T4j(>csd9&_R{sxH1>52E>BQMtFC0 zb>Z{g z$cw|}2SD!zG`lBcb`|}{*1|S_FE-7+R`LOeXP;FVwI2Hzk`~a`iSH$Rp!qCoN~~!i zYsq25nFbYSrK~2L%pQP`?p-y@JaTq_D=p1%t2auKR7^RGfq`Y;67F%u%8mM*1%imi z$MP87ygyNfvx@IC0TzpNb^G9XRD@pB#!)RI<4Rwo&6@yMRb~d@+yq^!8PJ(T*Kxw} z2NXzqM2(~Z;Y(K6rgsk8Q1n}w!-(GB5`P1@)@dPz@A_$-Y_MKIkc?Lm>+J8aBJnkd zl)UF59dvhDu7vzJ&dEdT4)fD$6k)Ohje6x+YfTTk(V%^N4Xi8+8vRJquHwO&@3{Xt z*Vy>`=jKuT$D?>ZO{>O}s4W-3^j-ihYJ=mko~Au%C|s@kt9zkx^iVX9LXifiykhI% zXVOH)PS{dO1~(56C~ez61L&)%wx+Teppoy?xd?XZr4tzqa{A?*B1}$`el$qqNU$or zXJCx^5tVY;gJ%-1evGNxyn+QZO$p=UO*E zz+j?xg{;1rw#f{e{$j@=ySmQR1-lc?h1}n|^*Z??LqZthN)VwI`-vRvcQ_BmDOM@u)ASP$HIIF+d>+~Vq$j00;8XK05g^aFC-THK^T!nY1qj!Ehu zb~jamiA0I0GM#hWlD5O8cJFKU2{;OCw4kgDDd<-+?vu)^;X4>Z1kMrnLd;Yw1 zeEbU{8(Q5&3ZRuNjvsPEO6ED)nu`P+mepccTePLSu)1Vvrb*2wYwFX2J&Lnp-h{uV z*rE|S6L>B3iN#yB#FoR<$J6O)-WyM{M%&n5O!&tX-Rz6l!kiQFh*DwYDfXYK z2#@$^kLC+6$u6HflII39&wXS%NoD8w&}Zk>qF+$f(i`&h<}N_UNs`h?gj3t)=Ig z=S8Znx_duy!AEDmDPk2=eIwo+EC7 zq;Sc!{SrN<@EI!u3A8bD)6clRj;1=XPc(33<%I~}`cx#3cf~sXC>n-zKXNdzjWmLK zc_C?>_O^NTPRNqNYziXYqGxBCZqYi}Pskh(#HCmUf+aZfYR7OnzI|XE1+b)U9js@h zp5LTDkAMjIUQfT5d$)xc)sd&c9(D7dj`hRimD65|S3#T9HM7a#kSdmXzi~7DQS@Du z7I8422m-y@or@{Xgz#hM@yNQu;ZdJH9sN!IZKwOr?Or2=w3+Wa%s4En!R`e2jE#D3 z>PxpbIZ|=IPQV5!$a-Wmiwcimgt1bCC{_!m)HvX5L=rV#x5#OM|<}MJ; zv_pXHSVh2d&!+Xnbv`&**#HB{P(HpSWKM!#4dsTR@<$uIgU*1WK0WW^P?Kh8NPKHZ zW~O$%aN+zI$#-{sBVppI{&xgLG^DTe)u~?Oke=97m0c&qw(_oZChunS6=pCq>LP0* zYqLI*?ipmyRjtU99q|o=f(I-Z!YNlj2tO@Rn!m#@pym&49uNJ7ut)B;-uo0+2&BH# zTVOD?QYiO!Ub_MVX9%uA^qd5Fq8|xWdm&eXYiU->dwH&VUnSJ_ulIdBhiAN`MP0DV?0o-dxmFZCn zxM@{`bK~pxKK;b_y6`g#8>T)}?*3#XBL@?_DT1I9DJQFVlkgp4P7d$Pj+K#vQHp!r zuvgd_D`lH$NYS%Ma5mn>J3XQQK>t{?g`0~0bbo5N&vIGA3DeNML)>DyVX@mF?a6## ztaz@_N#8pMuW;^{!&hJF*~`(w*i1MVFj6$@e~Ny1cNLm*a8_E4^<4cbjzNSo%e|Al zj5gCuN4WDU97jSt(@=cTxSl!W%bkoc;Bc^9KrJXL@Mk83%7fjw?(P zBiv`5IA^l;kDMb-$j=~DyBDJ6(JJN@3!fFetbEj|O)V?HP+6tfx-X|M;~=)&I6e?< zA^UNAD`rlyd7@!DFq6cH56u41IVPKy<>+-%oFsJ|33>PD+x^T;1R1?Dbzn9rE^%IL36y3F33pxL>`ZP^(j@giQnF+AhjpsO ziyB45)VCOEn)o|mym}L>t16U?Jt(r#fOZ#Hwj0BaJbUwk`cBlUxxP741%K?g;s+nL z;FXxgkENX)U$)qimznxe0zCMp z_yF$&?Y4~HZs6g(=IiJo--QveDeZBD^pGcQ)9-*7&ztwVSqz64vt|>FHB<9j5W8@V zG8%^4R&Qrx*m&E;T14N?Z+8tN&c5mNpT_y;gW@Cw-B;eqOG2@kFN@*&0xWR%7AFzY z$nT5Z_+_AhgXrIr<|K=^KL%uy)%17Ym+NhyLz2)}E2*dsPJgs~CV%EyW#deFmh<%s zbEK|VBLz*Swuk#kl{R(!=#n&felO?3LlD5HU630@G$y0ckY+ z;xFP(yNacJQT6Ppr9zv~*RDp7+CPu$^~*-AZqbiqj8VTbY+7mo)AoTx=|5n-LcMep zf74SQ*qhmj8ir??(5?yrpPHbmh}6(^^kkjXO<0~lTkQH3PDPMx4<|2rHe!+R>wbE+!g+(}nb~d?J_8A?K>OKR zCR{LR{3n}7aot|JL76YJobZq^kYK1uy-puq7juMhl+W01G_qiDI4}z z^||hXYk-6B^;wyNX)hfPT|Fc!K*f$cU-vvY|6JoXhMygc`X*MGZN;R>xb^h|Kr+3& zrvCK+A8behK}||kDhp0*zm&_Xi|@sPGh~ma?As)YKH2m*h}6Y%r%7NI4f|L`iA(Yh z?s{Mpo?WT8tBZrnC}}D4DoIuA2FkI_ufdl}qnH7=rE9t^6?uL%h-l|E0=@e%NBaQi zS4vdl5{Q)Jk9e(N`HY~E8*7PYeW?4>AR-Ko_bojs=`t0HcVkEU`t4()FYT^Gd5?Jo zwZ^Us5B4DWQ-g0gL=t!GIsCCA&+{&;Gv2hDC(3i&rr$&?&HHQO;{%-{J6f31R2X!; zCi1s5)Is!iJ$EJ0Qw!bTAEx+;5?Bt~kdMVohb&ong*&KXtzlEKCv3U3K*eK({=ubd zNd?ZZ3=fvt^;E@fQ)R5(p8(0p2(^qC?hn8lieO1g6=_PF<6e6;P56%P_mF4qk;kw~ z@hlFj$YQEts5dC1+Sz`M>T{U22y0eal9fQiuLxIR^+9rbYIiabi(yLyO*U-2T$bcV zZ!!F$_72lP=*{!!K2_JG3@Mv^wy3AK@K~DDvgg$`ioei1snm-hJ^Oq&v1hDzBNH^P|8oD%*}_SpZ12hW_fHKIYl#f6z|@;`JU(`d#)Q9T5Z+Z!q)Eo7tYg|j* zz5UfRd>~>C15SY~K8G%7m1p3~{fTE^9yR{*%o0aB#-?N`QPJo+lw7XtkG{yZD3YT+ z0WSQKg_v(TQ>FN{0N2=fIhC~sfO7ANXOd`K?~~A93DF{DG7l)%Dw_SO?P`nej_oia@^34o zbfJ}h@CgpWoNRT2hjH@UQ`pLEM4^c6UFZcn(gK$^S!(AkwhqJYijW#qc^ztvnj3oj z08mL1Zf8B4Vj#A!5twdN4aIq$q-eocyiWtnB2(tuo)`pu6*~@;lltY~6s$8}R$ZMK zXwUXzBZ~&#Y3D%ycmc#YxYQUJ0j9(khS^Ul z2K{xrQIm)){7rr4iAmtHf{>zeF(?f;CI|!<`7IslKM&#^cMbV6BlwAkmpE+LOR#N? z4bP`YF)?6(8o{DghPAR_xS0cY7|6#5{-=oPYu zlwNq_9_jF6e31fNLhl`Y%n{&t%6Rylsctb+ks3aW8H9D1zeQtQ!s6o=`D6Q~&o{zOyC#@$Tf$^}F zSAIC(Lh)j7>}KPux1PI2Z7xsl29Dl`SPR^QrFYNU)^l30i+y}COkGBt@I|j7Yim;w zNypy$p{IX7J*A`@>s$G&#AeQJVKmuni{lEv)r_kdnX#fnlQ=sTHTDj3rN?upx+b88grQ!ajnw6Yhf*^&dG{0i@~7pP`oC5EOY2QZQTplm#R zNzs@B?Rf{AmFou}WcGMhWIUVCcyEcmJPZFwAc%czy@^Gz8Tb)Hjb0FekzmnvO>7{k z^JiP}?7R|g@&Q8kK8Ox(|7NgdYy)@rQO}wb4KcMv=%f?VLP+$@a3_SQ4iY8GHtC@< zmBrn{{3?W*>u#Fr&W~?Htglx=CMWOx4yrmuAKA*Af!YPEcfi1ViOPo)rdt^F4Zlg4yRrQ~T-)e*|Ja z#(lP6Z%rgy-O9A7UT>-ONHoD?$Tf(|veR%O=8vtu*aEdba+Q>9j!>*mzyG7svfh=> z)?0w(7hK##E$ZeLR6i`TAX^hBY3&;u#M00>)jmaPPuy7@mGXLWb6sF$nu98G*M~W) zJ%Um4`R>m*D-n#D`g4yoH*fH(h(S~$u;1}~FUX7k1k}6T~z(mF?*Mv);2af{QhYbe6|0>O(`|mtJX4yav>2!C-wvx2KHpV z^Q9gv$Q2ugkjVKL9n{4+bB}W`4>YVxjY#TP!Zp+aJhsGV5^fbQV@mAir&8xVGj`{# zGJiWsW|zEX^?gYq%eN8POoOgO?YH&xCnU1O`|x~xc|vZYVDiN<-r!cc5(V3+=^7dO zooEWI(f*I1Gu0)N(vyY`RIN)(>?c1AR8D@m^KE|9bvs<}1%kcNeb!qJ>qr82U#dA@ z3h|a}?4_SGO-MeQ{mraz)bN?h(MDU#%K40eIH}`38dy9NUHCw^RTi`L{#n&j-B;_; z3M)om9KQV{Vf#sVp09 z2+bh}|Ig#AbGx;5j^$>qzUN#S;5q03K_lFc}IMi zZ5X4HF3haw32wqV$Adj%PHR3Pqa#Z8i*<*SL2Z7Q#>?*38YDc7Bew;(nMcd zkLBS?u~wi};ueUgXEXQZ=_*JH6vBT2uajU!_LlQ*1uZid)3s2YK3vcy&__smKUBI}xRH_Wh;TnaD z&jdXZJMU@=D+LQ<3e?0qd>E}{dj3eH20E<4yk^e0l*f;{XPK0zr)z8ipgh*paAq1( zxEV~{xacTi-RM)yYPbVc{>P^Rx_(aGR_mV7v|!q++l28}p?Q9;zQQsGo)eoUMIm8k zwp~MleD?(D8%iJBG>48c=r=>(T!%M&klQSUCV!^53ZDj+Ab4!K+ zN2QV*%&V*JqYYAU{XKF0>7QA(=kJ`X!}1895H(u|$soW0=?Cd+UE1|M>N1C~)Pos| zAF8g#`X2xR$5J#faZUB{ z3S))1_^!IuxT2yH`Zzz`_{!(y9^p}PAMmLjb;`_O$%`G5-E{@?UwX5&YQFu1)OGS~ zi{TvP7*2QJocVhh($_bQ|G$q5JE_0Qka(ZpwIf(Xd1w!!%t+N?e1g z`Otpu@w#>JI*;O)d$WZLXTuqoN%neUDSn z9dXNLLR^hn16HKJM%R>M`jxy`OUEOoD_5wuA4{P@sU_rPttXR4iI)<+v+pRAOFn20 z2A`F(#g8m~GzDN7Y&Ij!s+Pyx1>7GmbN!sEoX7i8Sk=U8o8(6J(saNtP@Xg92>*Cd za3s6b;73XhGZ3VUX#8HOHyMEYN9GxQD+7Mg;D{@Hl5nJ%kb3(!Xx<2`caMVbMz-Um z!e`Riy?Jfij@h>(JOKJ4wRYQkx-7#OWO z;o4;V1Im)j*??Z}l@a&f_kCPxMI2G*O49phh$YA_YZ+BGtk4m^{KY@9MhI2MJj0~=(fF0f^AQGEkn$n{;~ZqU>Guhh2&C7Sdfl z>yzOmx`Y2?bSPe^X)kMW<~4`miM>YkS>RGT7Ikdq)^zQAr(jh#-s>r7#624wl> zr~iOU4e_mPZIJLCr~U2(9(>b)CS2LzHc#YwGMA_GDA7;*0pJ7`fk!oB0*ifUJieoS zo}M#zg}J_s#OV~r*BM&i1x)de(hHRwX??Erf8h5xN&zp_UeC1MavNpg)ll|7QH3D$ zbYt@jBZAX2lX zr(ky2)0?ly3Ex`D$~{aD#GJAXl;kEPjiBv|>89R~&)?@2-io%3ot7!Rr@O|wkT>5sN$tqH|GMH!frGbK5Pr3J!?`>~JaxYuemSeR`At0K zDn}*8pH>_7BcYw-A&IdC{+#)VM`a1?L7T3Z_kt69I@dulWU-9IhT_L{)vv$2RqO$s zGD$8;wyXcxKHj6V>Px&)Vdy9JLeM03A~HQ-hMEHP@$J;8?R1x3P8tq#<}G{)OA8C_ z=f^YOe)v-`1irMGoDuo%lS}K^XW_+MTl+=tj}Oy{VYRvL2ZbSn58w)i$354W`O~$A z4dvwDeklhmIDCeWwCALR9vJ5xdcPiZJZp&2jJe<@eGXwX9~trr7TfZsA(l;xR{!J0 zd#kYin?Nl><@;RzaM?QmzXkoOR28@B{&?#kz9S08kD5@z@rmfCcq;aV0@gFlm-K9@ z2YakQJQ2*I(6s^hfC?Oa_Fh#T3f}&v(XbaqKv+!9gnGmSnywZka1f(3x-av0^|QVf z8yN4pi&slKGj-udxZrnwoF@eR5rJ3duDb@Rh>lIPE~ze0&)*EkT#X=ZSX6eMTu$4rco&)Y`sy_z!bp!+3y7^TM~m#| zN#ww;f}u`!SRS}n)D@IJECr6|>bZogTcjk>uN`w~G&a!cqWwJPH0ZB(KJq+*T|iFJ zv`wY>Pd8?gG!a2X9zkTH*k8~c>@Cekp?*ww5r4**LO{S$}79j{~+ zzXK8CPeSLNX=fk_CCOmWAgp+D(z$5ThQh^{P1g6b_d?ie^3q9W7JsJ47E}84kA0`y zllS>A8(pjtF`k1q%w$57{gbjw`h1(Bf8SKkp1U;p6#ZrzZZ#|2b=w)Ue{5!v<;^?0 zv#tBbF(g2}$PO2USq30&Zo^TX&fI*uc+ zn?gNqW4Q!N3-7r}`fn=u!LGsN?v1QP%Gb40RYsD7p%97*Cw8VQe#oHP` z$7=1Fm3Q)5)A>aKh6Kut(wtViIX%p*Nsr;jynyD)f zZ|J}s79`{&ztBgaCmqwb$mF@YdVT%DHRE!nU$mm+x!0dRvmG%W!nZZp%)2_F2MiJ_ z#T%Y*;SJs8Clk*HBKKYE&iA4H?LL=XhvO3_6YUFBJiF>jU;QI}EKQ}iCS80kD#R&R z$Q+(&u0g{tt|UABrs&nN{q+sMsZor!bJzwwcee?2A`fng9mdL~!T55%me#_Y*ChTD zT)~+>9U%88tCBA2hxwS-m6v|2@BCqwwxuvb*dWz5k946=W!HF@;O~PJhoYq~xJw4V znrd5@I+N6HYf>`lN1Cy7r;%nEed}MfClHHIhO`KoWoi6{FKDvuZ}f#Z2v>4Xk%8GB zsHK4HlrdjHtyQF8<=M~s4)u$l&z4i%hH`nyBAD5*z;MrgnR`k~8hi? zZo`I8%ne@NDksl%T^+gp#`Be*uFiZHo-PBc&NST7FIE0=my;2_xJelAK=&D;r`+~> zNz(7+N#!(dXDY!bg;BCCA1G?+H+`Dl?36=6+vb4U85`REGDhRDS2XE(Li6yhm%TWj zu=zdLM)wzO7ap%Fk%JF}(k60u-&Cp%$%PpsTuoSog~j*>O6ZgXG!_RZ@il1!M&)^t z8SOhsAFu*>uOUDL=iKxh^JW~wg2&54S& zQXsNjGkHjHCqX}aSRvhKp?77DjwO7Y=h$!;U(f0owPU{?kfw58cj_eyErBs*tOl{K zys=pO^5@%oZmVRXHzh6Gp_f3mff=gma}m@9`s8hBRs*6 zU^0CRfC_Q56lpmjYdT5i+D87p8or!fCGNC!ucF>xl<>lm-H6^l_fID9GcUeO=zbEn z()Ue4y?u&AurcKJtKCdst6ORIQmhL$1A#Af?XJUYiH0Cc$>0t>yc+&QLurW9HRI!_ z`)7wG4Xw>t>)uy6C#;KIseq;}11R=nv4lzD(n)ufpm`nd%ZoXr<7xAE0!LPsm)<}c zgNu7&PnNGln5VZsR-V6=DN9|_hC>2-ZtxX1FO!#w*=I`vDNvi$?vwMzyd7^Hx>pTH zdA@Rqwf)srTEPo$BO;7Zt0^hJJ;pP0kxF?_Qco|&N=kgZdXz7{9mM44gDO6GneW8B zfO9)IT6cjAcoA+xdIf2|YG2Uj z-lPrl*AxS07flC-=VhzEHG3%BcVfzVg3@ygso!ZYE50oHrMy~-U;6j$95abBmDJXlVWKl*dY1z2k2ZChH|T?wWu70p$c~9Y&@hym z9zp*>b}2Q%XyWT&n-sybU5dAa49Nrv7W;Am)K&+iFqW z+V;>G;``Bj%g)-Md-WOJ_jcFTNQL~pB7)p(3}=h^nz%2ZRnKvYn~OsB69)0jEk|_& z+Z8P~Of{|E{jqq7h;SdDA{yB37>v-T%52CjBYkf!@1s7O(LL#ekyAsES1hqt+|j5j z!jMRSn$9IZb(FLSR`n6ICDggZbKbn=x{RWyoOMmOUUf)qtTW1UJEf%Yte99OvkIa{ z9VuZJ+PtT~UU&HV@qHL&l^!L+mVA5sQXQr~FGtAC_6*HpWK-M~sm@7qloplsJTrZl z12M3}kB`n@puHkl7OH{4J@?5ISYl zaJyAt5-;AZ&7UTMp+T$@_$>5QS9Db;%)V?r4x*ukZ_kxK{HQSJ>GPD=EvXhMunIKL z^3PZGHgN>i}vv@D#bGujkUuPaZ z!Zf{*kq5v<(PVg5$2h52&bzcdrC8pExOSwPDImE4jhP@%+@_Iy{A)w|q#%0+wdd!~ z@$bwP)LCG&*ihs_#^fdEVdkyeWe5&-%5&m_=G3Ncbg=XcD`nSKxfx4t1zd*M-Af*` zF;rZ3Jb;5XC!manf>WIpbWD+>)4yScBAIuh&F4~whJ4CO^6`h^$@+D}He zs&9{dSJtSTyDC8t&JFjLmn>t(s$hiD+nt0Gl`V#jyzvccJghaSsU~_PsT5F;TOoAY zBcaN9%BnMAnFW?YADm#;{o-){&vz6Z&ygX13@eOxb%uT#Lz&(w8jgDbFkE9uwEMB_LOS9MguZvEnKO`*6 zlMOcqK{pwhZ&u|a!D)S=iV*Jij~dx4>6g;>Hj=)C(mcL?_s`BG|fm@O-fPP1BjQY#00(H2HG@2Ua8QgD@ zEd|!_?pHCg5tO9Eg^=@jhaip|5vHV@dWGLu8~B3|T!Lt`hFS<{47~fxS0(O2-a&^k zHyp6s-kv&#Zi-3W=tbLRuTMLijVrKOe;JXBnP5iRLIZ6&g9ljElH9&N0+H{zpr%@b zxxAqGq0nyMe14jst520CNoAn*R%O)UWc{)4-Q~{x`e?%o*6jIrS0ohue7pwf8&5I+ zsw(Zh?Rv~Wqm!x=A}>V~e5g~JV$;UOK~Rlw{Ia!V@W{b=j&z@x ziJfs>W5<8oa0p8tw?spt4oh)t>?2_rpEniMv(A=$_*GwuPPKk@vj7*F!7g!!a^H(S zkr~`|*fl2qq&KsV(NJdK*UC+pR=ia4H5W{GA**f3y0M|Nq z>;kzm%p1vfByC4KhMGNna)aMetNGnybzsSRW4Se%X2WLgJ3Gd%2nphf)~2y{r6q6j zy$_6|Dr7F`nBsVA*p6r6i0F~z-X-~QUaCc?=;89Y!a_H%olwBedN$^w;g1k47wJ_u zY)bf!v2^97$AY4I{$C~d>zQd|)``^{HWT5nr0CX|(=GbA0N9bdnMJ^8i53-dR;zGg z6uA-cqIk`CSy;6nZA!r+VY;T`OplATJG0g;AKzk6J81HcH+#Bax`>4T6O}&xSL(hJ zJ`xU-MgDYx+SJ=dhnuJ6LD4nJG!0S&P#WFZdA$d~UWV&0{T-9@Un_dNrbn6N5aSh-k+zlBzT8|-!wPUbvUfN7`J_+x{ap8qCKEsuX@C8=yADX+to_z! zb3gCBOQU zj&P@Z(^pY9Mc~pZq|wpr;l|I%>Dd7YPZ6bRr)x^4b)9A7ptxzgi!Bjjf|u`EDMNlD z*f5KO35_-T6KlOOMengFy`MB4JQW>A3v6ggY4EsD(2D6+-bxs?lhx59l~CuaGLFB+ z#Ukek-5jO^Fj@k*YI>Cv-s;eds+~p`wNj9-*liErfbZfESW}&ON;+hoOi>s zpMBVAWMW_suCCE5P0uUl{sB`lpfSL*f>2r!Q_-si5WSw^I&$do&RFS*bMjcLeHY(v zQ=3HXz?3EeToWhCc_|lsKmxAAf*S439pQS6;eF1s7DJw2w7831d_jvglBxYclFL5v zLqikl)$!C#^-+bqUARwMsg@e?-Ouic6hv4mZUx2!D@k{!y+j3bSC)*bp7nPMVfF9= zmY@+Zjp?5@`t!v@#X~6Ut83x>b2lS>+2S8wyBHd87(G%;(T;D253)FSI%W~8eT^Zl z{AQ)b`ma8nEL5x#+_havwq2f`SG<;Uwjg(!+cmA)BWBsG5m(T?i@JTc-D{ilYvS7t zBP-LwEHt6GqN591YZ6z-Y5Rg&t^r~ZyTH}RK0by`+4~63w@t zV9k)6bL6qTLWu&QYOb<6gs;9bOtkYPZEce%4+l$;)}<&1G-}>@g4z<-dieWT#o_&o zP_Jb$h+HCGg7Z|ZH;dxK{rK8651ehWr-*z#NbJz4J;8j<%2Jy~9uTGrMlkrRtI)F` z8OqZp?2jZLPZjbSB8f@|-qk`0cSd#IqZUFkFSa=gFJr5r?-k7{fy@xY8p4)DwSqu0 zqj8)5H*SM@&fV??U6r$ge#=Is%H>P~{+*y^;|D-(YrMk|bpqX)^wPNxiq*=``f=K} zPR!s{UC0aGKaVnnpsNPWov1@Gy_C4ao5AQ?BCOLLh7dF8qrugc(4Sh5c~l%d@q8-J z2l6ck@{{)6+9a?gezQEQKIQ7QW%bsCmy{7p{RlJ65+l{9Gi{ei?zIufDxJjMPF>g+9B$CLMzbhBmZPb(d@h!qxT2=yB&K{Q8M?ut}A zZ{=MRUO(wMVkymd|JB!{lM=aZN162*#Cm(NWAGYbitE<9szcD2`^|U|`F{c4Kq0>- zc8p4_q#}ZSjt{;MK9!YL)NGBY#W^l*j}_JaD%fe3_jgUF++EI4mBMA&PB_{*1buVP zabG)pQ24jv-xEu163*Tj(QcgPD@QThmCFy9fw&KskT~hrt$O#wUx#;k-GuO3T%ulD z%l?z($%GBx40`9B{Qx}$e7EDJJ{a)^fu_XD%VK9S`N{Ig#n|(zXFU-nHf*47Azpd<&zklSglI_J~!=Zb+MGImUSdo;c0`uO0oOel2(_;l9@K zKB0f&9Z8d7#FCX)#!m=@1>>pDeru}@%_jL{c}bpjE()znIa)FPy$_*pel~b2$%vQ4 zHW3wF#5}ur_2#PT-Z8b*ZPt5BnC>mu09}|tNd^9zm7G-3?2`T#>zkd zWYi2&Fg)ig!RyeRa%<>sgMJFsZQ!%iJU^~oO{P!Dx0-J-5udq{>FzkL{B9Pm9+H)7 z#lJ7rHbxee8OrqC?frH>melo-Zlg&X2!J!bI49faD;LC1X!E>M{`5r|RVp|woc{n? zJawkeqGCyu{$I`qH;-|)4PRu)K(ZbUa^E8d}uOH|9it#YmN|?&N&YA2d z8gS=FQ{yiMSZbPO%o0YEMJk^$U!xP)4%PBUj(i#7p9N|&Hi@WB8$t`g8=cL8&J>Z) z(z;C><8O|9L#>NDUleF2Ms2@ix@F6IWG`Q#uG3k%@ja!tnd09L!#0@QJ^q^@kzyqM z;bLr&^R{grj8q z^j++?UnG3}NXC@hYR>lZ)cXteN4Fj&i^clP*V05RtRk^nONQNW$g%vT&IaJSLV^c4 z9XtJ-q6S?yBrI6O&jBZrcDYfXzzY1){hfX#Uig1edG$R>1nMymUXr zJ;zRK^t;2dt=^GuI=7gY0L&b8V8oC|;6;9YnZi`@GK`FCM@1#GCY?xZ4CA0ZsuI13 z&pm48!fq>p(x7D8e!VNmIg=_njANjxtqxe6ewC!jpL(w2X*}^rqn-Hu5q}5xPo`DL z!T$iRV!VpPgh9qhIT){H`0*D1019|mVT(&W@{1=Nsvw(h~=iPJ2nZ&h-L2tDw4BO^Jh zrf)?jG@0}Fimv=d`lBkx4gRNnGZQ|RjS>`AJZ?XGqJnTnTLU>Y;+nU^PZ4KNwAR%v zphuQQwhlJkF>+KW2Xh~tvHj4eAXlO5UO$sf)b)5J)uD>=8KX%cMv+n%{^$#kNa^!* zI2o=}!MZ&E02O>od8l}vQ9L#bqQZM;Q*pR31QHJlIsn`puo)SzN{f{kIlU6Lw%5wv zdFpa1vQb*U!{&Myg=}=FrqH#Wds{Ez`y~l$ZyGd_Tu6kdJ5&}SMhdax0P-tO!uk>T zqwyANSi)TBx{doyb0n~`fo`CZgRqdU(U1Y%f_N3YJSQ%vq`jj^E%aM;V-=KeD?+S< z5^yueJO#kQpI$zJ_&MN#72MbJ1d?KcBzRE9igEK5Q<9+Pxi#Wd#i%6Vt9p8V8=llK z*XH(`CFQ^4vF9HUJ{UB51^%_7TD`l$5f(DEK;SDL8AchmDxe3p53PLqJ|Osq#2;<9 z@hzy1EygJCq9xD_6P7`h{_6rU(2hn$evazi5?g&D7Wa8%vDvLC;Rd2D@EPz?NSVJTvyWU|WeyVb)X}pd+yA268de zt#}uQ>@E+47EMIn+h3XGwzf9w6p`Ivj$3g65I8IkBNfwl7vk@VJS}f8hoiES&fETs z_azZyQ<1dtM&1eF6O;M+xY`veu4)ta;``WneCg13tqaCWx8QO5H-WD2V$_AC*D9K9 z(!~wOn95->yAlfLpi%gCu3N;4VZ4`9igstXM_2vl5=qYDMtD39FgoJ|*S=^T64hkz z{C2V0G^plDF78SJ=F1}%clPDIeJjZPWuUc#OQ(IEBPfAfGIO|N<{pQN^e~w9TC}3w z{{YD4#o#@SD9I~-nc~*hSGtXpL4^s(!V0MP>t?r<00>@?i?xo_Q4nGo8PLGZD1l zgPw6%SC*xhaR=BQwbxz38A$-HKU&1QOt=IwBe)bH9*gik*jxNL@!Ik-xj*;h*COyJ zQWq-2oSqNiUC+U!EAaEi*cc@aIsX8rM!3@IWL08L??GOjFNGXcej$-tse_ft9d~s! z3pOFjlB9jmDtmyDK?w@&hsNa{Ppv&mI}NMysLoFu`Wo28r*&#%iZBjFa!4PoIrm4x zl8fB-6@3fgN-Bjtz^JE-&XvOs82ZoyRhmed7@sYO8O}c{^FP`z$F1Qn2{oKEymRVD z?C4c@5~qgxU}K+p^;EQJ0LUk3$sV=yN9|dw7$?&#cB7RoERvAPCehOeq5LXYQCglG zrs+2RA-lBEp6V+Pw@MMD-JBd?9l&F$2Pd9AF<+qn0JBf*?WX)U(Bt0{O?@gOT-*=& zYQvHA0=^#j7x1n>9{fwvVDo1hbRWLCfE=+-$2jY|13htHt3DFaj*p>R+q?O)#(_(o zryc8^`_i%K#qvVysiEb=YY0?8=q1u*8FUX9mLWr8VK2!jZzK0ds zj|y8IJm>^urWB5VQzUT`0>hT?>r>c3XD;)m&Q9NdtxJ1ok|K!}PSexgsLZ1c@R%Pj zha6Mo#BwMkWR5AT3WXa++#YIHg#tqCL4Kb%r2%tu;d%4?bEUT8RcB&2{{UgD8{&jS z{6yDC?{GVRu(i?rIT5FhbdeYXbc{|r{Eb+@6X7S~4zk_+{D0$%NYW=F$Po1F#ap(F zlDPdTqTHA1`PHPw`co`w!p)P881*BHzi$X6DJK}}1wPs}k|UMMfyt{7!v#C}(XhE*(a>IFYsS*pFn9FAv?rNr!VLkSfCdqK6inES(lgR_#xo;PI zMX-j_*I2Y=YkS*aFPO)UfRT@Ct#R?AOz@AxXmuuK{qTE&gN&9u56NrBO+KgFdpW2@ zLOSRkEwi<>Q*5$0NaG^}`g#xRUnhJ*(i-ztxGQqZq?SHLU^R#jl(MsNur<0sQJ>BZjWv#6sURPK4)x>S)k zQtK)cfWTnXx;}v{(s@q1Sw=(lU_Z|_(B37t0Eb3lk25_#4uF50*4~Asm9|FWNfeNz zp1fnddUO{v)bVTki1QmOk!9jni_21CJ71nKeSgNiV$$K3IOc_X#EDg8O!5b2{{ZXP zlS`+WJVSiy0huLYKs*q8f1g_PZv|aQB#dyyFh)lXoM-EfgnDu-)PmIc+(SLv!Sc2J zyf;uF62Qu3PgNvy^gVw%_g@2Ac`v9!2?;LQmmiV;06x{@{sPg?pCUcDW2eri<#U#d z5z3S34hZ(IXz*+;ZK*`0VO}7h9#2k3;D4QV*zy}Sr;BTzr21l!kZlSuIq6z=w%%mT z!6XW-Vk!d>^MRg6VNyv{#=-WLA20aQ%NY#E8NusTgiNP%5Jz%*RC6CO$RuEo&VVWT zSbm-OuTbzpl9h^lJn>$Y;P3ett+>bD{{Ya9C$JlIQAJ1vb6*h% z9uvIJP0{zq@rvndn)rw_;VaLqfBG1t_5;Vv1P%@t0~x8(BNG1rFls+H3b_Y?`BafP zbCL<|nu3WHF#WK3`c&}4^57m%T+$}q2LJ(qQy?HQ9Ot<_(itMgimS+0>x!Nf+W!DC zQb^8fD3k{IvFZ3!xIcM-$3e|89}@on!9+Y0E}!Br0enG*0O3#xI2W?}g?iXSjsPX(VbH zlHopR$OrwP2hf_p_#HjwyYTPB_ji!A7cFTT+(zHQG7XY1)H<;IE6T@3`>h{El}paD8gMmZ=t+#T)_dd)3$R1&r(zHgm=S=CG!hFTC|T zYI8YVEet!Y9!aO(sBjJx;<&F8czv4dlaHzhw&%}N+g20I20sd?gpX4jcHQ$Q5 z9+NzhYMPzBt4J~uNd`x)a@K;EyA!&DoEJQ_M>~5Mf;*WSG9%>|HQ+xLZ^2pAsdZ(* z&3f;SKWPsD>H2o)?vm^f0Vpz{dl8;<>t8zf)8ki#JWq0|rx^%wl3qQbPfS-NaJ6GA z*zI_lQj1qUM)-xM&jz(IVTj8goc{n?ag`W;jcsCF_b->T{dREho(aDdAF|d#Mueu^(Xu*_E+{z){lvQ zXP*S$&of=zeTYFM%-JQQV;TB=(Z~4L<~)syN|5=mmbce#KrMe-Hl7 zUKdGAF}Z7tr61i^m9Pi>^Pk3?WaTEArD_qULNZ;?WGLIg9OQBDOm$#D0A!J$>r={E zB{}7JBNTzg-f|f5ao6ix9$3sYLp%(eW7?p6qYN%N!QJ1`)bkj|a;)vQITc=H-7W(i zt;q+q0~L@z3C2%R(zN_H5M6%6edZFWC(^Q|kH}SZ`Ba`paw}iM&7Tlh=e)plqy^6w zL?6VLWcJ&~`~+1f5mar)a%)G$L>~~|dX2n)z(rG7^BB)=_2tjwXJmd9O#%avgZWjo zMJIt(p(;sS;Roa5IZbNSR)>biyM+s$;bLnHZSG0+7C&m*rvpH7v*R;8T2 zSC5)P+5tvJ4q+#-*k4%$~%DM9DSFI^WbeZ*PrzHfX_L^Ub`k&zlCjS71aic?R z8~Mh@D94q-2Ve)BagMd~*NH!4gQP3HL|`orkIG z)1Rn34FQM48gxoP*%E?r&T;Eoce)%m$PB+R&VF7G<~gmf)2T@+l=rdaVk$0q!R*=a zPsAUC9whO%#Hn?wi!C!q@cdRr*lDq8?`~dWCg+k?DsoEvpefoq3;~nqAF}7d9aq9v z_t8rue`Kq9iEc=BQb_|3>(e8zBhtQ~)O-b{>JqD5B$EOE04&Uet!!9n5LjD??V%Ay zJ1=}!ZG3Jg6HnOA$~t}@sf8y;45!?!A@a;887lV6*k62IXf)hyE6 zPqvxiknNS>Qq0-yg#_c?zeIm(?NMxeAh0tr^B4fCdEkF8Yvum{4rw;mw!`IBkaLso zU71!bW%8Y88`-bH9;7HdP8u-1uXE)802_QK{?FGmohI6Q$sSaiORKlHYkPPEY8f`Z z4(5=C0Z0TLqmoWNL*VDc&2z!tEtkO>{rhX0ESQGg?ouRZ%P1l@Jv~A97490Zhn9PN zw|1~!qJpdE$Cg$0Va;;)J_oXrWH#0o`g=wzOJTyOCN^z7?@v8 z^wIwSGU|^$8C6U*Z);9kew~jA{i(D&eFDbL#>L;rlI5k2HsnW@B!TUaE6hAAqUtf} zX?YVgLR1W|8sUR|amGj^KDF%Mv^9$AaB1>fHW?&j4YZO@%ntshxz7ec1;2%S#hMvx zrff$eaY=Q%r6_c-*gmd&8& z6;rqC-}=;ZkF&LQrS_{+wy}iO1W{V?$@vsaB zqjC?ebq)!UvC#Gv^GzOGPCJ!a3;+jA^z^FI$DHMH&w9~j`AF-5$E{M4M>*LM#d(#a8A3*KIvVvKjLW;jei%b$>n)E26J8_T?wQ|1{G*;F84XVPo$4+q`^t#I~#tfuns4M~H zNgRylwM*2}o3xSnkMaIixbfk%j@hEqt>=VYOL3KD01mjp1@n*(I2pxvKe4^x@mIx- zYQWp0*v)6S#-nOsBr43f=t{UC_2aE{A0O_do53kRHlV4g3Bx{k4L zG$Kn$=i6@`>KF3=0CJ3XNzO?jdM-~m=_-{c8N#-4p5S-wn)`P{@U&m>k7=5uvI^d~cDJJz&?0$0i#xD$fE7o;8E31D#8#Myn-Z6pZciJ*Y zB=xQjM!xaK#Ge$~%c6K~<+Lxu$!u6C&U%x8Iq&tZm-d73CZ~D(Mnh$92iv2XZ?(yiFVoteuLYzIgeZ z^d9~mRB6(L=F^nb+m}z0IPq?yl$29Zi_tAF^JE?}@K3}o14RvMHJy}SeqSO@t-_C9 zGoNbtlg6Gjyw$alZLHg&)gu9Z)f8a_qaDEGKKxg&Yaal9Df}-Xx7qeBHH1aDOiIPgRVj3W4=a4 zJA+<{@l!yTPSdY#qy+34`GybW+Prqo<+Q23({9d}QGp~FvLW6_l>N{E7z5uvpGy5d{g16L zN5OqM>rzCHTlZ_R976$FfDSQ%w3c1Odb3x}W>{#`N_}=_k(W22?YBxizyME|_>XGO zm;kIgk=*vH*9>Hhf`U$Z_a4=p)4IchmdU{572$&_ynTCuYdYl-Bz&9>nKhu&1BK2z zeJZ8xyC@~F0rfqpi1a^%ym$k~x#Q#~KlaGi4KUf|?{I*ef;-osd?|>pfc#>-WT71Y z0M{d2MaGjBr4(r|9zzBU4mtk-3iT-b2;!^p7MT^qY9DFf=N;;#_DN$Tt|Vp>woXs- ztr=GkpO|mY%0Tq2?NQPjPdazo8n?|R(m>C(ZqbPfJc^}!)3rw!?^cbv+`}60VV}L& z(!&g9+BV>$4hTP$O7SZMWnuxqJG&7`1fEBT0IuATf$d%&`&;M`U-&Z1Q){CXu*e}; zif$5a>OHZH=j&eX_RJuU*F9H~D~kBh;TQ48!~H`{g*@AWo@_va_ta!^I(Pi(HK9?_ zoOkRAqD6P%t!q_iqDz&W+80$h^1xQdK7{f3iu-0wO4~})4aCp26?pDg`T^Y6#{U4Y zmXE4k;aiDpqusJbQXR%R_$DC1i8{Hu#ZkZ)YMRdGkm~+FKYo;=FQOuMldNEiJZ|(nq_bYDoO+qW;pfw$xY7 zw`+$j{;6;Y_sQUWPXiUdck#lzih3i~}z|)yC?&YT6^fujWOMk^QMcZvOJKHJl>i+-1ytgVLFiQGa_ZGAZhqAk&PkCC8V5Kc#;1Hjfgi`3!61TW9RC2o zR-f?h(No9zJ8#Pg7?F?m8lCYCf8w{*h|l`({ghD6U~+Ru`^@8<=ARs1YJt;($*I@p za0ty$9BNoD+_pI;k~AG{2~`0HP&uoSF7P-2_r*CPR8>_{NEqCE)b_Cw#EzXRfU{_z zFvoi9JUgp3)Nf^CAugy{q?$sDk8A=?G3+aj)jT|&AkwGP|z(|)Qmd<(VPbBBoxiJ#tjrtupcq)_SI6oM8yTo^1 zCB4x!gtdK4u3`|{d4^_Vg#&v5fypG`SHfQ%d}HHH1IKdcy045v>o9^|z*|Obqrn8D zJY#B~)84-8v6K52+giPu=hXFUx7#G}Aa_LvfS?ZDPC5Z!IebynF1{i7ra05XDXQvD z%MaV8({{{9PFb)$2Ts-Vs=Oq<<#X>SU~5KKq|&zRweT(r?~VQe)qFENk!W-2;Vzo? zW0XZXS5K)R5CO*|)+fdP00@1L!WLQ%pROjU9f%@H3#x<8K_nB<{*~`v2R;vIehT<; zuK0^nv$462%uv9W3B6+3AMaUva?BSa`@Z$@_r%W-Xrkj<)a^9OJ4j@POBQ=*0&m{S z%K_-hIqj3`Yid|^?GpKwQyC|RsZuRjJAa$MUjG2q&LhKKIla@Tmd@Jk^(i1mg;jt^ zhx{Bx>7rNY|WvO#5b02fhO0Ug6*|1^Ud`dp6KJ}{y|$XN#bc}_(je2k(DOQh zkl+uzI5;Dy9>%^|)U-+TyUR%|=9Qt0j21wi7Pcjg&9oP{nu_g0*hxWM zs#hdu@;8%eYROJ_GBhco68A0ee@;cQCqRfnNN$5E1TQ?E@ z^+&!lRV0gJk&gM|pvTp^MMwp6UlABDgs%x18>8TV zzO~ZVJMjTG_*U#^9H%4w@jxCk9B#_QvE=c`6?WA#8mn-_ryXhb@QBo@UJvpZcaNjZDbS9(*iDNJKf%VUNuz*gX z!68Vh-)B=JVY>1`HF5&L06-b&K*ca8Tu0dF_32+2`0K?UGWc}fBa2JatTc@SPt`9` zWVoBj2+~YtDl@?temU-I?GG|CNGBX)-n=K`r^1~h#?yF%P1SUvcMP`?-b3cM4BlEP zf6Ye*xiK=d z>t8~A3;5k}@owd#njvX4QI{zjmfn4a0UwQFc%#C$_gYSu;rqW0L#n}~uG=ATYGf9` zpW%}$#~H`zUXAcG;p*sj%cu)DtlfwKLg1czpVI(WlUi`8Wd*7AbSPD#o2c~Yc$e)b z@gK!M4=%0*Mc_-3h>NM*IP5X$`B%<<2JjDyJ~Vi`!pa>M z#VAzv5^=Gt=qyxJUPp-@>uD%#baxYMHVHMus7o@!vVJew30vv z9N=PjTSV5pUw;+6R*)vgDAT9PfPDvA`zOU;vgW(uYvR|MvP%$L7mzjp9)mS&!9TOL zuYoS4nt2{l2g(t4sQfcp&lPyPElerp$_*zwqr>mKBEA*So-3tU1129M0N2afo|_Jx z;{CB7^mdexPrp(1ud#n<3+QcQFe7aQ5J9hxbvZokd3iZz9liLia80!2`kr=ZqNf-| zY<6B1(3<6uZ7p4|b;(LvLZb|05=&jl3=2N#N zCDC8+E3BYC9AQsdt|ca72qAkBRyOWt9B1@35Xwl(#CnDutEBNjB9%O-i@r;kBa^a9DQ>4-)@e7y}vym>05 zA48h8qA32{uqrw8*FUWYWxo}F$i;Vn2|GIf0Jy~L2M4DVtTT=Aj;6X*#CJYm zN!%C%Fa$)o+|nHS1>@^nPQ9*4XC1Z7*GAH5qd#R*o4k~NkZ#Wews#!${5hZE_OS$7 z#CFnvE$r=@^6pIi*s?Oe?+`Eta@g-)9S4lBJWq9ZsNT)xJjK!o(+*-x@G^Ma#~)5B z=kaaxHjk^o(dMR`GyXkz>~aizp_Z<~u8G*AheyS-Rj3cM?eAz9I1){F+ydH1(QX z-lf`HI0^wzok$oR_%-y`#a|LL-)VXUiCJfP{MMEJW4oQi0l-o7V?Oorzr*or*jJ~J#?yS=Q~v-j^ES*IjX3i3Yy8jJZvg6Oo*uCCSP2>x zBpy0}T`kXu?X6P}AXOZaPAkiA;h#=ASJ_#bHizcN7*$N>yd&e6#%sR`qFKUap7Qf6 z1-wJ%a(z8J^V+yD)2mg+jU}nkQwL70omo8(Zuq79PH3J8gxlI5wcoiB#)x{c=soMv zz8qZYcb*c{^<8daw>RjwK2g9CD-5cBSg(yf1$+qAyl1UJ;-3}}(r0`Ypygu!02A+C z_3>Ln*R)%ET}w^zJ?)*PvTc`6-i8T)01g;%euP(TUP@E4mor zZ@&Kk@D5Y$Fd46#`k59s#;(dQm z)O9QK4D+8ciieZ~`G9%;RhwxQ&Znckn|$%ym(TA6VLpQcjE`FN@KhHk?;X^hzwi#n z`=p@{vU_Hgs9Ebakw}t>6t4_B)=sZ#E!33+=cppQr{UJIdEtxK(e7ksWh6wz{q^gQ zsIN@awT9H;*vc0J?+V7Q3Rr6PPVwpJdKBuZ!8;#0e$h99Bhw)3ESD!{IV9{S@$FoP z!+kRHZ8q{7Ox&Xa(_2POkG~Wbx zveL^?jptj9I_}l-w>E4FIBag;3F=RMqtN3bzeSBX$0?@iE4O#|H~nd;@mRS<9flwekI)op?>f#paI90l&P1WYPi%*h%E%5L>oD z>(;$8MaR;-zxHJDU8jq_6zO+yNgL`Rc3%bi-fH~0KT(7D*Q!hRPHX0zWf#jW(c@OP zJ4<4e#1;F!d(|tIEOLD@$6CEBV+S04I@NO6Vsq4Dp_wBi;_~kB=Z439$NvCDir_61 z?)JxQb+1PFus`BK;otX<{()Q#y5M!krhC^!)}%*bXf4N>2^^Zbib)$zG5XYTCP*E5 z=C4B@!f-gxYJ!Ku7C_Hq_|(EOahzcKP^w1*h3}J7BxXRkJvjQ*v{4eo^hls6omxBIF_q=^ZM=suLI{cZ>%7IzHKmh03 zrOMQ5Q-5hQ)5F)ap?-||D*NH)kK);Erq%4D)RNSeiVLOR5O42oJQI&vb;rYv8r-+` zc7dhZ%OdP{NCJ#=)D90*T|SoKmmRB4Wl*4wU$Cz#jU?fwhoMsuH9dM9PMP3KT|RVw zF5k`#xH7=GQ;ZxOWMpw&R1hoZ*HNh26^|a+rby`Ia;0ElA*XPWds4Quw-x@=19t0M5~4tBSv*1Typ>BRfqRewD{A{|fR zzKyHfV)oKIn1>=c!DVm5HRfI;@NR|SD{Hx}?4z}cAXx0c83WqA&s5c|;nTMjRZs{d z`d7<8v@ec@rjc-wVO9GN?)%X~H7it9qW3bW<4z8&mdDB;7&SqCE~zm)go@Zbk6E0ZQ_AMgX z>gg=tySNdgqoibxUC*XUvVG{!3K{@MFz@_&tHn2a$F;U$|vjIs2a(yd+re*ml5Fjt0H4LyFgXPMR zj2>%C8+gbIk6tRg&*g#Df#6dS-TX2_o&xb`W%<0boN=Gs8swp1m|eUT7!}(5IAbS+ zd{_W0guu`Jay7|83rn~<-~*L8=Dj)}0ywJtLuCa=%)5_%I#hEgcuwF-u;_UJ)$c3@ z$z1y6^`<-y;hQ+^j`*&F3z=VIU86rJ;fFn{QHyjt7cs9RJ?hKbEU0t1xH$xWo|M?j zG(>F2*XuwL89{`SH#u$vOA@5AEN}Ayq!sN>TX`ACRocCdGrE#1R%A`Vkb-vs-he20 zBTt9Iy4C%Z67CZeoH+Zy65Jo5&MOn*x9r>CpBZYa;;#}|YaTGaiFTxKs?Q2Uy}~R* zIX?VWvT4)W{6&sLF7RJz$`x^t9w|zn%t${f_k9b)31Ov!Io~rbTPGk_i)Sj6No>!h zQjI!Pek#a4=Dqa*9t#~kSiF}s-G;5-(^No=ZgNl zPiy!o@KaCteW1k?S)!ON!iiWAbL)fn*UDeEo!r*`F153mb0F6vAcWYh91X?>U>M!czi{xE&ad4jd`w^040PWLb$*Imy$8ZC#Mz2 z_*=vt96tRMyi}o<$>b zXRdj#5!d2)ZSr|#Y}OE}1p4sYSHBiDonb;cSZL0X|_IJZs6cnmGXc=RwbB{MP)-X%NwXh$UGC! z)`tMIERh(CFdp>OwN#KwShC|ic;=_KR=c+%MJzS<4sqb{`aT+1!{kXl1%epyNJN_6=C89v&g5#5Xc^#jRvKN*svo!dXCj@*%eq4P6()=QJiC( zbgQ=c!1-!`zhZ-MZb1hkulROIw5Udle(7myts$_ul;SxN+jo>$@Er+d!6S0*BRqj# z$ul4a7_N@PQnu5hm|Y^g4-;=!8-W9{2ZLPo`FTCH1xy7WYi7QsBl3EsmM>z$fspoPTKl037Ic(%g+brqZP> zM%xRAfPdd8zbLz17T<-0NZO?X2!EBzdzL4rEnhoE_V9>w#Y}1xwm{ zyC0)e!s4Za=bLVB$uBqlT~BZQsJvrqpm=;}R*II80>rFaKrDXo#yZ!*zCZBd+~_jP z7%}e5r)UHfKHrB*?7lsGSG@5riw8MYeXK@EBRIevsh%L#bWN5v&nErxD?Z`(2>@-! z=bHAg>zkUP=3-!|Qid68ZT(IM;dZN|U1;B8GeeYR%V!(!DQR(mX#PSuCxMu>&e&Vg_p( z@Nt#XwaUP?TAwYGVHq=eKbZ+%v_T1Y^^h_HTpQY`Ue(D!?!Ra6tJ%2RI*Ebg8@Dmxxe` z(QJA%*%a{P?HbD%2mn^+ZVw|l>_#zJUMIJkO7K(?F{8kK~Q zM*dN`0%c|X1|SB{<^1c5_>-m`Ls8Q7qR9o7nl;_U$ZwHjjC1();Cfe~wx@w6rzDy3 zhmVqfg7WBA9vNg!S~x|3j5b#@IS_y--y3%uMJ0Ybu8BR+G=_6 zZ#y=dVyW#Af zCHVPoMTp?8-UoBYu2&|yp(p}N%ROD2rI*Vw(#aVtV`?gX;Dd6+X zK`Qc2Ggf3woFC4aHUxMBpGx$PhAD%RIOD!4teH|rIO43vflv%kV*{w?wE$6$5DozM z=dE_$9bKA4Bi+CBBV37(3=RnTS7D$GX>kvB{$`T{Mv5q@0Iqw--|{Qnf4v|6hAW}2 zd&h%57rGeF%%A!gpbscuLhb}LN{4#}!S%`hUev1==)&`#UrJEkSUik(H7yiMN~(nb zvFblMnPYc9FgzTLcc#Y5`$~>GREFe6-!}uNtsow-oD3<=Jmfy*=W6t!~K1%U^W!t&!1PARK8Z;T*CpfGR4|uap*Yz8?^maE9 z*+?RibsxI(dXxv$ahmz3<3Gi{V^Y4h@Ya{-M{{=&ki1~vMn-or^uf=+73lu}3;bQ7 z{5SBHm!;gwVYQl2?Q&Ou?Z)Rlc_8!o*NCqxG_*eN_i8Tk)a-w0#)5qo+2l_#pg}0x z>yDoF;+_%l&x(E+=uvo!QPZuY@a4|Na3wx;YR$ABcRaFkXuVG? z`1j*6s^45k7Ct~qw^Dsgc{hS=?eBbh;nci|WP*FxBa%1eT?~o{KZZqL@rCfd*Cj|~ z^AK-Ao^m~ZnXK&wf3bL*NSSyrT|(-A-E}|Gy?QWI;G%q%Dyyqi%>AwKPr^S5d@O?I z4-05knly91WH2c&CJzCfiDCy}P6c!mdAT@H+;z?>%S-3Ru20_^f$h&f)~gvA$x=b% z8TYR1BzVoaJH1HLhAwy+>FG^p5^mae4{o@rNl_CK$O9PcDg|G(~MV_ zKaHJn_)$1qg&y@LzzOY0gB`P)kOpsI{b>R5Z|#Gx-DqAWxv_@# z0P*Qwd+@n+E9=ODBfYJl`K6G73bFgdlgAumsp-UTEeKHo6GKH|BX2=wm<_&&F+-t)j(mB!nM9!rfiq&V|qVp-xD z>Q^O)vG%W~E;RoD?T->@w}&kHb;A%k?pFkVQ&(D@T)PtKy&ksnO=!i3sTz^zTYkUr z=Y#wx@h8RQ_`QAb^Ih@Inc+vUv|EcelF<+LiezBM&4JM5j-v;#uc16k@XO;R`@WrJ z;~OnX)>m~8du}2aR18aP2N_~iaaw;9z7P0g;#G~D`o^6N%=RaAQ^^o^jC0!@^*@0l zy<^|_{_DcNU-ovdZMrhVMQ?JKY}Cjfolk-6f$-{LR!=fTYm zEqlZoLY+LcYVB_(9ZP`9Hk0Uc#e08`zCHNq^y6V|d1hCZdDRri<$+e{xEvFV0gkov zzOUgg5qw_NARaZ=@3n0%(Zk1P`(uc(P@{zdCjbnb_wH-y^14x0oqknKZk6u+KjF=B zk;gRo;S~CI{{S-0pN#B&AZSx+dPTj&LI4>jl0CVTs0w@If%xLRRbrIb$Gv}i;X?t~ zo=^3v8fJ%QV%ByR@T7KjiX~{(aHAX|{W3p6R{T%mYYz%&SGvxlAcoG)HkGr~`T_2E z0D79{#nx4-MwJM=Uq!puW&L**CG6nkH|yB>YxbwrlJnvvj-L?>G}}co0D3fxTOW{L z&bjS>OLx=kwL4i}D6{2BEHVXjkS<5D3^T_EDsfm=x|H5D@rI+TYJ`b(E1m9#_!YVj zqKps1y-PsS4vT*#kEz=%`hC)f-DM|hsXQExoZ#eiHTqp;{hNlPLwP}K=ls_BpAg%{ z)SX_EfAGURD=+q(7Ix2dE~=9K`7bkrjtY*1&AHEzFM{-l?l4M*NwLCeYD&D80m_Wg__kLRDQyq5Y)Us z@TK)lMHxS~oo;Q+oHIl>1!BFjFn#l1M>)+`(=P39^!s^i-We@f0Ew;0DYS4lK@127KDAZYrbjsy&LmOz ztfc539|QZx{{TR)3fVq<^~X$CfALEP!`>gr&Po3O&?|(q86yP!Yo>dV9gPT(f-u-8 zin$Csd1I1&`cx4pC(w?~voQ$8&!dn{3*Rqyz!byr2`Grfb-O{J735iukXi$Ex@bUbm7Y zoEs^fV{xCEP_mKeK>&m6QDokxu$7u-uYx`xTI!k(hVag_$$e_GtAmisv=V<>+}AvH zZKPT}k1F|?z*2c8zC!(%{BSQk6{2bPGO5-4H9y#-R&TxM#LXIh8?ld3OuhJ*q3Ifp zl-@biuA|kjw_L4?DG|bkMpTV?q0f>w_j80jRVB7 zypw8ol93j|3t*5vI(8LK>*8*ib)nAi-^DBga+it0108$Um^bYS;NJ@Pc^F(pi2+qb zJCt=9&whuX=n3@C%|1K$zhv^=Ug=ike{IN{AWj*B5)_cF!97Ou>Cp-WL1QFbRywyJoc&7Kk`Xb3|w$fAn^5?u+JRLmshn9(tcF+aV*KfIIP@Q(ko}vUnP+nO(Hnx0m#e+WD0{Z7*@zCX>IJ z;XW-WnmvRwxQ-3LPb&P|G1nk-#xsiazk#0!yfN|aeJ@7Sbt~H|>pQZqJFILxjf~Pi zlt?)xP$|jx73G?)fvb4S#Aij)EpD}Y*@McETPK+-s5!`9{=9qFsD8vA2i1?qtsZM+ zXfE{mWs>IJRVn4hgAKeNR$#dG2ENj_xrcI$?If@Len-MeZO@k4GxayZz8{0a+7*VC zV$Al|aV&AO;FcK4Cmdv)o&X_1-o7~Wt&-tm0l8o@X)U56C0PDc9AH(W21a)Qp2Sze zt#xMXf>2HwPUa)?tlNn(IwNGBoPULD%z#D$o}B&_nJNXChTpNaw%q+I zt@v=n_&db}j*5E!0M|2I$k=^1AG~YSq3|Pyuf$f0NhFsnR3eT-^(L(u7GRCg_adT& z6+>!aK3hb|rHvx+2F%hsL-;!H)-UcdUbXZwP3~&iQ(wJgs(Tlb*(0f&N zk1F{r0ppIetOlCEsg?u+I#p7N?#?nsaf)ggbL9mkMmarAOB`}8?V(4Z9Z98NAEewz zX{=fKvN0Rkww{Ba82^bknR0GmEdA)PBofv`R99bX6aZ_zKc7bk(n`HJkR%@sGN+ zM<=g--hL^z)g;rkZw$|%EP$##!3?Fb&@kiEt$f4dPmEvimuk|f>-$&ejxD%mp++s0@_H^6)F*A1wqFjg<||S_=BkUA^ycQ z&;6ev7z{}fpXe*2v-ocg!{lnv41WydWAm!FehMNtX-&MTj2D7cart!>5tTTn9n&kLRgPi_OENyQP>#~@QgA&L9R3QX)^x+!#?-|DaOG0NEGDx^KjP4d3W~HPv+g0117jCe}3XIo!RtIg`p5 zBXJyK1Fk{hzG97~XruIueQCFTZ7i*8U(VP60EaF7V)$KU;(rsR&4!(6VQ7pbXSY=k zCOVcqvtJneS@0Y>cZ}|hh3ujxY~)H$J^9Ujx$(b5@Kv3x_Lg$^$40o0WsmKD*tb(# zx?y)6>Vyz7-N#D!{{Y824~L=gY_@t|jUk%XVJ3UacZBC73(A0d=hGGF;pHVO9wsJq zr$^qu%~iq>|&W^7_}wR^Au5(>z6L9YG96_35>-^AEzlu=p`{miDsSK33w*_Y~+` za}~%R)9X%*m9BMSX5YGdoz$OY*butmP73!wL)7f;hOTd>*>86eTEralvPl4M z#kR8j73d5~%uyB0O7yIPjmTOq% z&}{9R@zzxZUg4cgSpNWY4E~k&P$D}h)dvAbAl1-=O}1m1;$rElQQhkOIxpAm8zbQd zQ<2vd9FMyvJqK!YHsGoU7^HZDG4IWGpEMvjQPkk#rV;$7-k~f*1B_?Zriso5K+jqL zV#n$;T|SC2r$#;7`I^B<_X2wTYoO9sZH!~w{{S;dfpUr{sQ|8f$Adl?x){z`IR5~F zis)+t#{+kUu7~?c{{W$i0P@A$pD!al>J^bhm~+Q`in5=78R&b|b3_Y#pl3W93MU0g z0YLV_rxXRjDm_kpX_n~wa6lOC(xznyGa)5ULIq8LcH+ta89nn-1ZEk?9=`O|b!Aed zjMKRo=RUN+kx(hdPdzbN-ZSv*o+8=}E@gM>H#Cuekibokp<7L(dA52xyu5WTaHB(!p(#t*2kpucI)fcJWwvUtP8R-bEd8TD;0Fn3Hb%+Z0>xcQWI z`@@{)nD{N?h&4|NKAuWEQAM>`PUez7Tpr+`O7bef(Q5l2Q-QAv(p=k~cdY);vV2MK z5!I~xH>~Q~be7`w*_T=K6@ly`JsE$yjE};+Kg8d&#;fqI8?8e3!=lC*kX#qKyId-k zz!~)i752`Hsabeh*HVH_Q&iCY+I~yz7h}UZ@$)h`ATa1i8SP$S@mEvQJVAR5miIb_ zv3U}CXISwIf?;0%Oez8)I2mkbig(lE(D&8~Q>m(tFY{Zc-*3m{e0`+&C&ix;^_GXp zT@Oc%&ijH7nB%9(o|&&vmqd%4qTw5$s+{yQydCA;#ePXX=N1hDUC#CJ-AgMa&!6qb)PhT&cVH zo*8inH)jWvmJB`fkMr+KWfT3dGhmpIza6;ZrMGkz{(OMDgM~u4EPXRtdR>8d9h?1R zgzjvAo-5FttrO>I$C^j&mxb;|qu~u2=rJOD3wcLAv8l*EjaZpfChTK85>Gg;FZO!z zRi}==2>3rzwQx{r(OSzI9GK;aL{cgD1wSGyx_f1EROG1R8P7G=wO2gWtnA8=WGD>B zlb)H)JmmE{kLFx4>faD{{V!5Jx)C;_JW}5wuI-2 z7xSbApArH!+oBKmfAkSmU>F>OjOMI(k@oA?eZKEG{{UoE7K|Km_}7;|jh&0(MTO2l z>yJv99oWwt`c!eNdt)6b`3r%bDG2lb0FE%E{{Rd%#gMQI5O7g)M%D-VSAuvd_eB9- z?g-(E(iQVB?y!+T9(pW&0b)rV&IU7skE%RFrbn%4*LHFMQe@l6uZlct;W>0YUscm4 zas)RyjyYQ)g8)$dMlgN2uP+_4K94K4NXnh{-0Ag=X4hGQc`Rg-4K6ap?yf)%RachU zKH~9@UO=yvz9i_^I@4TF3{DbB0gB#1^CENe$a-g|9ff+wiacJcZ*!&PY%F86idkWd zZXr(Q+mYOWyknj#7h8|*ejA=B)9n+;v9m{l$0QTCj=1@F@0@d9UIH%-SyZ;|eaFx> z%?A_ZzaHr~z5>@Y%|l7MxVP1PW)0+7U;}?hEZxPFYuMqL&C$ULlG#)W`4AdHSaB( z?E6@-;4!ZX_>=HjeM?iC?CDH0Ni7~XKfXcstA7c8J z)yUfA1AjC6QJlsYnsMgpbK$wEwvo`^{jEGp9gVHTGsimwhVUKAv1g|}IKaW_n)@T+ zJ+0d478+lMd=|RBz2bRyH=4QoJ+l-!cU{4W_Q3DnzFqh=pf;uBXf7Vx?K^HZ#J|^ zpk>7%@sM#+D~w>|RagmSJ%)HK-lswseB7My1u!f}DwhCp@0y10C6k9xN4U)@#9 z;8W!yNQQksI?atA5qy8}f_xnDx7+kf6QuZmSc#qPEyHnU z%DSGv{=U`lUxf77J`euT*Iozl8-=vHVER4m!-)`*B3I)DuyzyQ3!a%Y)3??juQ+S! zy8i%Ok8cHCO4w?S(UykS!k^h%_rl&M@Vo1=Nw4@rTeb4#g7RnIV|Ks}3h)tz^*Q5} z&MWCu{gHkb&8%t{l1Xt5F>*O)9 z$OLxJq4lfxo+;3^1p?<&wznx0LnK%6{O2cdUELTA9y#FGnH+4Zu4%n}Y!%Wn5KM_l;Pj4zic^nsBbg~Bw6?~X--~vGk2f441JZbQ< zUmENBhKb?L74(fQWft(<-$Z`UrYB(jV9DA_xICPkbg$75ih8$#ptXwf>sYt{07VS( zL8rtQl2n77a6wUu`A@~)6(G63y}hxqO9t7%7T1JHg&;ZFy+9QW)ZrH!0Oyc<(-917xMjkRYJ%c%6A_Ka zJv{{1B^n325kxb($(v_1rI)%c1(WRWf-A%O%Ca(W-7Dk<|B zWMZhJ8P8g}5oDFWfQ9GW)k~1paY;0aJf-L5T$5b}0?!jpKv@ZH03Nim*%=`LxN-93 zPZe(8X+bClX56Xn$I^w3W=RUJ(0*)=qJSwy3!qTv86Xi>OilB)(~R+h`qbNG@}k&J zJe|WdJ7fi1?;LdNKpelsTPJ@Fz0^yYEl-+Mbt#ND>CfR`4SvviRlN4H%LHoj$_^ZK z75XDQ3hGgS;9-Ld=QZ+A?I-Z6C#G3^1^90yMiJqS7Il?m5(Tq~T0x%W zR2+|5^Dh_v$)5%E&j)yxO+!M{>@9?kB$tw26lfJdBMx8W`WoSWB7WC;W}foHzTPQ{ zva#~Y?kC^4ub*|F+8e{#fp4;DdRF$3%v@QfUH<^QPBKn=n$E1@C8EEX--f`}O*dA{ zxAgx2L(sk~_*dZ9!#@pcaQJsXwec>v{{UsTwzaWiBM`{NWHS@7R1ub7d#F8eUl8cO z1}{7xWG;1$Q#aEB(#35lWEtu=e;2vwpIY|+026#ii&oR(owm((18zw2u>r;aUH}6b zz|S@0+W!EEu5}rjNo6g^UfA>=g1qW-lv_~hdev#tj8mI(Yq`v57O82fYnMQ9^9a*E zgRk_ikHTIZ)IK11vr6#Zl^K%zQ=M(&AY?92%;(T5<%#qa%#!W$BAxE#usV`!^fUHF z{hQn2SBJ-oJVkH+02OAZ1|qj%&4sza+5Z4t8-m`03+rB#DZ110N6%KR95ol+-p9~7 zK96tV9}MZbO{gnpr(4Hs5&r;T5GefyXp{zELC#k`m2PJS(2>sWIqg~7rHz?NhQi?( z*SE3qokevqslsKCBkNF43EFZnPf|Nn=%mI=eeS}u=G7V$c&;xxECX?IH?p$%*x;@j)y$cSYfuFNf=;9TAK*d_hoPmJbHpYRb?`~--;Ft934e8Ms7^0iv=iWB0UM34FF{{XUz$(vI#qFfP? z{{YsjK>+~goKzcsA3;_lPMJKKM#I%Yk(0>hrCWsj$Bun{Y7rRQQbfGu(-CU)AFqk5f~=YWEb;oi^};{ zHp66RaVPM_e8oC$nvz@p0Fm}Jt1LxWU0qpzCxCd@;^pKP)~j=30G@Cp5rRt~IXykG z`Pa&y5&k0EYC5#YbnT4o_gPLAas6xQZ;4(Jv%5Dex7SG;pe9B!m5c+BIu1{I`Hx=k z?X~UXh6|xCK^(`lu+P_;RGsDTp7hkAOZQqF{pGfwbEJ8YTcXIzxtnMNk6~O_!hH%0 zpBG(fI*fnlT4*zrVZoC>AS3ns1$uR+g&btU95{`BWzB znq~!%NK~fWVoc>kw-@*tU>sPc;iWXUX#8NsST%Yi-d7H%cz8j65PncmL)*#p< z;{ieKlUqS5a7h@{a;rCEwDI<)E?U>amhurj?0@M}DgOXfYn`l4JGuD>{0q{#uMzw> z(fn`XiJ-rQHVj*!hyOjv4WUMebEc z3O=lQ)!!NT(q9O8KV-6qwL9Fqo!{!0sn63V@inbFYO}l97*(wBk+fgD%+C^j)mm@B zopR^HqfU-XI2{h26D{Z4=MFRdpF_tCmE zY&$ZXiu^wKv+*r_Z{o{>?PY&x6 zD(;!^EpB=&o|{h!-+}F2iD{wp)030CcRx?d;Pv)Cv@_uGQH;6H0rfP}*<;2BOi)2M z0f%4Ctw9ew@s2sF(T;F&kyfE4hfl;%1jwH@Jvy4*(?%^5>VKVJt8F8vKdo-*M>Z&Z z&-0|fw?!0GfK~^Nf8<%Z`ltScD}JziamR+Pjx&Ov`VgQGE{sNmar1PknK|T)obr28 zM&$P7dsEb&4nXQYv=llqy<3lz42o&PFFijz(25>HeQD9A&A<)?Fcl-fz#si;vZ@FK z9KWSUwV5{$UTMZ~q^{rz;1ftg!Uuew3Z5}jL;{j?noT;|Z9&>N)VmI+pab01-Cs$Q zN6_zYJn++`d5`7!RFVdL`qW9;Hu?@J$*8WSN%bf+=o(qvM!&){^D*`n@~6Z-IXo@# z1-wC{+9i&kcW@r+H6%wI8<+dm7?3U)dr!H1D>{t6fKcHzKn(>~O?n_2_>Z+17kP;tzt_qowwrae1PHx(z`T z%M&Q%2gfSh41>of>s*J3KWRyCET=aU!1LnI1mIzpBX9$dK(Es8hrbd$FY#By(dyn5)$O&52I0Je`^a1SvPOPn zZ)P8zektA`GFIA=A|K%;NF;k!^y@e)J&p>vWl`O3 ze%wnISR4?`*o;vo3MX;Y*Tdhk@5c`pcu&Jxd>Z3Rt?2UZ!dy8r#sMK&T<5UlbUk>l zviv*ZZ7;=ELgP=l4D2%T5(JT+;IH`=+Zm~zT;Sl^WvH7nZZcqF0Z$a^nfHPTBd8Sr z0JAu9!~!wF9jT9ua=1%LDrRU(@xdBLwD ze;Yd^@S^+9M%7h6H-AcNT`0~^9`(kri%NK!;=*(yRg4($xhw%WyWM z&q@~d7j31XbbmN22EaV@9D+04RzB0BH&nG;+9RgA)M0`W@=B4$qa~SuADw*t@k+wO z$8+CZ**Z%tsp3U$89)Sq>x_m3dbN5#j(j;9X@VU`S-6frDOTgii(!!TJbwzGOyu#+ zcI_=4&$ z5u^bk)ofNdqd<0vqsV=u9D&1QBO$Uo*Au7PJ*D7|RB1OL8;gC-vIYn0Rl3(&isj|D zs^5Z3^gXz~WTbhY#p?tfG1J&i(m{J^<+Q8RNT&cC54;NGeLDJT_!CSJG*VzJj!&A4 z$Pb^Gk7M_TvG%BbEom}7iq52^)|+^eZs@`(H(>ok57dga;5*N@TSYp7x;F_jFGW3b z^dph@j>5jy4pPgbZkj*S@UiF8N;sEu+&mw38sZrg79H_hTBnEf+vhIODzkD*a8Ko2 zzKC~Rtb?2mMlt$VQ*}7<#?k@yHSiPWg=@jJbKISpGT_mmvysApsyngCt{2Bz*V)9e zLUM6{!?ks{(nzZ3Cmnj%o@%f){ltfoJ?q}V$C_$&9qe(vE|KD1G_V&o@~>&8YLEXxq5grz9<{=Xm0&W$%3 zvroC+X>OkmEiCRWqi57)ng`o~pS{o5zh6rGqv5u?o+t2*pL-GrvltA7bUjDmf)C?g zm$#o1uC-t7JG-lMDOVb4;DMj7y?uH6KmOK!2|83dcC=^EFL8#FK_lC@ zzD{;}W1toCc#H*lX;hSM`n9ib$mhj1Qa&HjXzikV_Zzi z>ySX{(yc)$kYFDDDx?ws2JUikSK?ooVL;=xK+7>7ER6LdrC8mucLgNkpo|UY>CH@! zz(d$`%>pGu@`8UVc>%CSIqlkzI6yj+ifEW)Bl14A3}|fe?nB2l^1toH@ZmM@hmm-O z&JXyT=(2A~;{(hQHx8in>$SM6RGIKZ`Wq zi@G0+G>uIy3*E_P+lh2jy_e9iA1UphPhQ_4c&YWD+0Wx7x6wq&6iiwYR|TU7p&;WJ z#xwP=u(TiB3fElFR@UxS`%5HnJe)QpE1aDEBk(^;F<1pkOB04ygtc94eFhgBCwdj# zryV!9&gaeEAkw@|J(}Ck1@HEcoJJW75SxZWFYx@VnBzR3pnrq@2>6%9n#S!)X{Y*(pS{?eLS>-vQAEwl+NZ!>uteqgG=Fk*10c0u+Bu&)sK=lfCJ z-@N){7b4o;U<{EaLd=BcW;&<^a(n000bP`-41O>8Z{l@`mqXMRONiHW z)>3}%;sgHNXPkSCgX>-CksS#j5#J)bMw)hKD@8k&*bc=258^%Qo%HUgj3Wg{IsX9b z)z+I5vJO;ao|B2+8k{`)5?7h)c8;Et8+6Pw;mK!Tu@8KI1?1%+w~@Mv-Jm z0>)4&LOIW_Yt_U22;r^q73P&IWjeNBy-wXg?Bs zB>0!$O*+aOi!CzNXmz%@wVNMrjb$l4yQvsBUI01!`8`GxYAWow#mU(pUb%d((T&IO z9`xBIbWnL_?)^BcR#%W}`gN9}Zn8%O)Dhf7vY|%^>KS(_d zRpzy`0CvSi z8sO!>98~M~M;NFzW62wR`%|FngWjVglhjm^fHvo^tymT#ZKNI#wOojdE_}vZ7u#IL``CPLD zmItnX-9OU3?g5k&O(Y!?xpR?)^t`*N@nMdAS_v$_RSD9Z4 z&fMVa&vONsDmIN+-7TME;(s0db$<}s-Py$>;Rtz`Zq{!_;Bk}R-n@Fx;#`+E<(@^i z+6g0mLjE;t;#b3MZ@``^)O3w*+IwA09kL;8E3R@G2?P~AK^4M}3;mUzQ)MKoPDmF3 zWANKp(x(`vdw7g&>RXj)dj6B+cy3{1B%5L%c!tROpUSX4BY67LSFmj|+C+9HDVfOT zH9c4AdVLA6G@n~*6_N;4LZoApxRd_?)~;{PGhaz0ld*PfW9>M(j6rLEXLkSBEc&@2=ooCraF8 zZ}qZ+fS~o~wR#_b&98*5*J6F9^p0ip_8;e((lp$(W>s-&pToKICxuqq!*)^M-;idC zJfvH)BmV#vJ(k(7n%=}%l9wScC4}RvgJ}dlUpTpW1jV1p8iIvDA z-Yn-}?<0LXd)Lcz+)H&c%I?xi>{;E8OB2+Z@6j$;?0A!$r!HwdOAm6uZ3mIwt!a9! z)>jDV4uZd*xUKFrFD)V) zB2n^|IL>?5sQeQ6mGKYYAByd~QQ=azMgz8MO!=vC5&O}|gOUz9jzPg4DOgAD>}AJ4 zsjIfkRxzLd09AN5?92OD_)GSd@cT)oIMTdJYZz<&2I;|?A6Ja==0~669FB|!e{@L- zfIDKOWtDKm=C|~-n;8E9ALm@$L=f3L_O6df=E6V6`I<}%lu<=U1z`BxXTx_RIORX| zAzRgj<6-{*6y4T32`qPdRF*bV>X$17d$148;A8>oU7enVW2UJw!mlnf=1KE6>(lV2 zBbKny?r*?kjg=4a$S}WOf5Nq`ygy}X%5GfT&Cq`eiqUJvcQLWUDaHj>m>1MxPhw31 zCtLVz?qRlxLMi?g?NVwM!&uVp?49;`@w8k20J=!v{s#x}u61Ygyh!nmL~GaHx;P{` z&whvAm6OnWJDyH%T6=ej?msH_7BO5xe}+N9{0~v=MRV69WzmoiZaWI~{{R(uF5kqA zF0JPK7NV=S&I^^1M@4bp9gk7((!8g{`cAK*N~?RM%#d#8?gkP;IBMaOl4)LPB%Vs)`%C33vE%J)z07FDk5Kej0wvUMumP)HD5ow5=qNTK@e?DPQ&@ z`_6uxd)L^14}KPCUko&Jr|A~qUP2_gyO$np%s+|GVd$fQ`I_s6H&btgL#{E{)Rx*en36iPCf;(rt4k7h2>=C2!jt^!_LRVDc3>Qj zIe0bZdKZhXmsNc(cP`0>PB~@u72Wu2TeP3Vc9yFu{h&-YFZ9o^w^{~kc%Cme#8*n7 zvz?qM$v-Hmt-LjG@b9^mZDZrFE&dhOe`m(Jgx4EJ_r_cB6x~|F9ZyZTw45I*WGHr$ z2=pM1gd88jxjl-zlQmT~N5noc@rJkX!^HMpB!m4rT^i%=d-t&Z5AV|RFg5>dx{LW7SjyT0uy|k6I zeLSHpX+EN0j&g;Bsv>d@NazU|$4{$*Uk@&2WK~Gt&Wuc-JC1h~k5Pf^#d$A}d>*<^k*9*nB*&5F#26Ox z&Mdx$z1Gjh{vp(bzMU1)4I)%!@|G|%06Y`a^NOeOZ@^Qh!QU5Z_h}{F=8a(b zluedt3Pg9h^VbSo=bnPL!@^Rn1sz+r;&Xjz(!aFY=gk_%gBSK?_1v+o&YTiBq(vE5 zNgW2@Kkv5u>&&bz=kQOCS`4+-mBQyB{{XC0(TBgkuNCT^7V$lYi!`OPhY{S~<~Z%& ztg4J#a9j?IRP^p~=pwn%bbW5jTeYK$?J`}k#O0Brk%uue3=*t)UdK4kHT0Njv%`Bz zHKOga{U6`g{H$*$8jdrI)X=q+tw=dnj0}RO_30`%$Y7mP z10TwX677wB0Up0zX_|zxK_FrB1II&(^IjVBv)uGl?v2et@=JvSaKY+*YcgkBJ60Lz z9Ac%j5>E=TIXKTsqjn^Dz##4Wr!}QJC&}1u9ZnC%nYl+&OEUsVCnVQb@aw~G;r{>; zczZ?w$9UF~Y8sBtgvts<5j{TZ zmGmKPwP5XG83ehBCPflw(~t+Q%=E>37>r7e5y3qz_`MhE{z&rbr3tA>^Y4nj46=j9 zn(~NIRL38bQ#g)AlwpqpX~8EMIT+@=N5noMKian1Ev%TgnngFoK+eO$DL+$__*c~* zw5NeirDv*myG>${TkAjBZXt3vp@b=Mj<}IA__t6i<}VOIBLzwCmy!B%XpUlZ6m~KZ@5Pc+u5HZmfMEs z++fz9fc$zdytu}xB1xPyTi270nIg0NMHRNUZEEgw!R+mn?rMFC=o@gU?hnBgn)hEeMd_9E5n}%yjyn4uw6@W z3b0Wbc2ke#*A?rYANV7w%L$KG)9+!Bsl>6MCqM54Unh)?87CRdOS4;}eott<NeVxZ8fy9PPrp|P8~@H9YsemA%Hw*wS39&S`QKYH-YS7^Q6;^fxNl!SL^COI{Ft! z@hn>1zfUIQ51tZoexuY^%T6jT$=x1o;mE}J%ah^14rhb7{{ZN^^J^9u2E7yGOO)`> zhH!eZ>;C{;>&u{@Vku_EJ?m-iVI7X132@`)AZH^z>sBd_+-Ik8T(nmpfI|!(b6c8q zz4h-9T1zk>0Lq6SpGuLMB3yIa4w>sxi-3)s|XMhxw+PzUo9RC0_UVVS5Mm{C#c5Q(m(=Fst?dDCN*098W z?w!`>UJ^dmt(w_ft0s@-Ap1EUJL_oEo}=DWR8>Ar4oNaLRM z#%c;~t|JGK4t|yLSf|X-xxhn_ZDe@w$G?O6XT?_TzxBy@D7}3nrSxY5@1)b=#UryjgzgpH`Rty?xLPTzwYkni;CZceIB&H3sqAmyZ{1y6IgUj7GT_&*XkQ+@f8ncWt#vC~ zUl7|zg=?2n9m6lVUzLx(1tyK9rOU2I=UttjhHd9S)5biNUC)dYj;9{|hq)Ex#~o40 zMXQD<0YSyeT3e~!Xnzsx^^038nIM|ZJERXAOq?H-5~t9N^fkLR`rNX(a8o=H{OC^t zhw#J*v8qoFC0=qjXC+APIOQsXSonMEpyy?g@>?Wy z$3s-FZzHvh&@V;68L2f(JMA$`JVxp;24shl2dM-3issIv_K4lyRSlk_C-9^zUt`?< z3%qmqKgAmkMnE|K0Ip`N77-p3a`Yp;V*bwzTf%-WQggM`06Gudo|Uu|HNx;%W0vh+ zwjba}1#gIf?f{9L09YPu6r2hbS_ba>E z{cB_Pjs2mkPj`l7{@hF;6AN;@$XXb zM~zcPxwP=Fhcw&42BSKvjYCqn2^{mPgOwXZg@Ncu`c^X4sH12klau)$Mn*)jiBx3c zlodwm6FWxA`!=1!9sR1cuZ#ROJnIdwh%~F2mO}}S*7iA=Fc~UBF~R!PtBpnwNrE#k zr(sTYVFjxkXjPlCiyJ&oEI{K7qdE1cE+mXZ0^`jXEsjM5Pk4WOF4&01#Q8_#>rr0> zhBOg@v<{W#*2SirV0x4=E;3S^`5e}++lw}EdFx(#;ykL7tWk$d99N^>!{=n<@g3{V zykoi<0^=b601!3gN?P3d3UOOA=MRkk01dRi6k5%DC4>>*b^BC9WRLYD?|wD%t^WXp zXVWzqA^SmeQ^(3PUw3%4i;X%+kY{M=j;6k3@h+7cUrcF?rgF#tu? zt#G%|0msg#3pPD|R`n*mOf6`o%Fmn3u(Onu;*Y+X)fJqT+7##NDIy|J;Dfh6A@vpK zJ_-G(eiM8`7VD*W=Sxeukhj?N89v7<ZYE@&a~sBMpf#SL@HUBAIh_}2Qpfgc3c6tG@o=4>s>v~oMG31a-@ALB6wq( z7lueT4DH&(?|b{u21tpTFas`lCvQRYrCT#A9nRPzj8(BwYNGyenz;javE}DE|P2NZ&L60J^-Ud;eRCz%%kt7p+m1ay{Z)r8%!Sw3o->S!hbCVy zbHDK)hxJd|Pfpg(t9WiT4JOb}WpX1`@`-$Td=I*L{A=VLCdXJFF#gY2Wt2eJm@@De zIOe}bKV**vf5JiGzZ+gTF++Le*+xeINSTvAfhnJ@eDU#%LZ9K~mcJ_6i+x7s`xg&@ zzFO~8MbBY|&TGZRxzebb+FzOVnOC!|MpWeWi~J9j{xWz$v<-N9YqAN3^&QWxdF8!? z*RSMT5)Vh0vi|_}>*~LZe+PVJ@e5j8oi9MV8gW3P@@ULatYe^3*e&$~706h82-I{~ zgm)Vim-r*D{59MYndM`r6;Y~Zo_KRbhf23tVqQthJ9Q`2*1ol^+4xgRmj31PBOD_2 zcI>0v*PyS%X0(LKFUqPiOK<@7HS*`g{{RvX5_p10ts8cmYQ-VPNe@E*0FQ5Pt$HZ% z-iIx(>$iR<)+fKaV$#ZZPdrTK-doF}W_1I( zIp%;O)3g(DC<_o#+^EHMx_^X)lC0}2qG9u^A=*ddU9OwqXtcB*b{>E3k$}JF)}p(G zS(p!-I3S#Jk4l@2%J9~^H-`L6XRN~WSZj7JB(~M8{I% zex31`L$|QhCW;RgLm%&A3FWQU2Qo&v;P)sG9k}WFX?GNv!xTZ1a0e=VYF`O>(^2qt zs}xm&#-AVK{LOry`!s&nT3^LmJ53v2o;yzv zk>$rb5UF&-vFxsR_HSdwePyM8$BciE^QmB4qKYa&D+k8s{wcekOsD>YD|)azaKU^v zbVwv+IuG{60C|eY6*68y`@ymTZYCjCoyW1JB8xa{n@Pt4M)KHu)quOTqtgiqBk?s(+9DyI7W?+|iC6v7LH__6 zlTf=Bl3(2C<&N2#@)VF59vYC|YWkJlGOam{NgbDu@vfXU*~sFsyd`ATIwhX}0QHhD zn)w*zx&F1eAp-B7n4tk+Pk;#r8S6^d3c&M#M|!OJcwIdKH4JWKPT3tvrUh%C3}}~* zWSdL1c{-O^z(1I-SH+$X(dV<0HHF~FAZ&6+4`dfu66Vtl-P$T&ae{F>K}(HlEs$oFo(^~Cb}E%isDvs^+}c7G%1T_g5Yvy%F2 z-FHx1n~9veC7f6aGr$br&lTV3e+RrF;O1HEv^zw&U-^2uQ7nVp7S2BaE7C8RTca?* zBe3pk8tO1%^BZgaLOW}#dR~K5h$1l*s)HNvLCvNGR)Nl`{Cb|2V?sWhb zY%D~a!i0bizpZcG+IjNeVS(f5J%5+yN%lgDjngNmt`0w`u7i-lw6sxu5D0gUI@e2Y z3k&%Xd1V0Lezj8C)D31ajyDcJD%gtLuZeDeJ5>{>u4#bz;XXlS9Or^MR!5I@sk}eo zJ9zERFSR>_vw#kzoa2wDCc2$De$nRJxELUseXrc(u`evZ} zi5+$vorPbM@7Ko%s30i_(hMY}yI~kGLP5Hj2uQbdjF6BN5Rja7GwJRaAs`{$ARQYy zVC?(s_xu67_qy+^&UMb`^FH3y1>LQ0P1yH88W4?%hBj|;z7Lh4j?p&T9N~=Ucf~JvbNm0+Zqu&d+~{4T?pyTa`el8)7B6=4_pFb5 z;;IrB@#mTu+bl6)0Fx}K_|ktzYg?!2HXW!`>c!^+FpH&hw(I`z#hY>Hil02V^UL2H zlHR6t(JjYf1Sv7O3TT2xeeTK=)fij4#N%5%Ni?vXPQR281qwj&!8|RR)+xvxy-Q~^ za|;N}xXGQX233zo@h}zR+NsiKg#k2tFYi#v6r{$hds5ylBnC!W+Cam6mN;YqQq}M}|SO!dWjVj{x(6vo9DX-$lxOpMiR;p25f9Ro&NpFfY zwF)H~)YeP*!OE1oeF?WgCJv~eB5GP^lKmtMzZ6!H9N%fmQcl7LUfy(#JPp8IB!8D3r` z6CH-X15bR;VKaV^`k)&&rS2_RX3I0w30=lSRVpN0bp(>AQ;zh7&mPg%)BKf z9iNviPn&HTTRT~KiU3Ce-sL#*O#K?6k#hM#Q><%Aew;jmV?^?-F?VaFeosPM!KbHMTp0rCX2gY_*iXG0>~?q`J0`kU zvqXKTf;LJBox!IlWw|69%;T4Gd%em0a_EGr9bdWi#4Y^E{tyvG)C(d$k zYxf^uJ>}s@FiCKR}z@2dE%)RIbnhFuu?q=?R)1yY2#kO2v9!8ah z{xZ?oZt9wd8)>+CjFTY6t{J4?oR_g;jQ3VMl-^fkE2*6{xRh|qj1Jvm`ERtfX~)0C zY>QOSuh9qMFM4TOB-~<_O&-JtYg~#<8W$V7qH%G2Q6Q(|`JBbO0lfVsF1+`a7`^YQ zwo-6G>>kH%{oCAlVe2FNL{PUa&2BEIf$^WDQP1w34$I1XVxu}0k<6_?-8|D#qQ%D? zyKXY2?u{k-IJCVxLqzSUBi&h3veIsc!HoEiys1p>1|=Qe^*LMDf>-ZDUpQHITF&h` zvLn(4*Is=npK75~R^HAm-LuO~so8jDKvw2(&hJ1Y1{jIQ`fm*BeZN z9cg^J0X{`;p#ZBaeHcFyWoTiQsUl7n7)cE>K z5Z@U;K26+l{EkdWEZw_;6HVJ>e5t&P6!ttd{}++a;U9ia_%W9@;A3O|>~5BQ_Qk%( zOYXd?!Y_5oqNMEPz*3rnPHN2c~KWz;6q8|JQXsCxit_Jrg;>}FI zPta(K@LJk=&I_%;&7?}F%WX@rH~n65NAbY`zr38y1NZ18bLxj2RARYXAXr)T(KBXT z00t2{SJaXkEWwVwyZsN4ev{d17U^h&ndKc3R*}J!N0wNUdUlR=zU{9omb;CauJ@>6 zIyOU!%w%$V&`NXH;MKkhkW|#!AzmmH`7wB3@|{_a_uE?&JBkz`RBd9%CG(i~ zwYrW1CS?X7>X_U4O~(%rD_ ziC3<#(lSahoz+Xt()zq1OszU7yJGQ|hC?S_M+?^8If*boa_O$JoT zbT@#Z_pdG{#5ba|b6e>RdncoiCw_H2|cH5+rMxpnbv4 z9E!{++Q{lp$d&J&?X{-%Cu@66?yMf8T^wOgD3ig{((peN;lU!Vu`G<|)*TvyoTt^l8r z@$=W0*TjGdDhDN|(v<^ckNu6crzWPAX-Da*?k!x{I8c@Bnt6(5%d^{#?ACy6z!_=Y zt?<^3VfKNKfr6&y_^!UI$2OBKcT<%bhleOlkL6sZ_)fwGVcN)un|{ysY{`NdzK58W zr&Qj!M9RqH!(%h8*w0+4v3PCFZF9xL4x=eO*wpY+qq@gTaiJ6HU*F6=ty6SB1-|=u z_K5K%{0ZvKW4W&HAyj@6r#KPDqy0iW)j>a+b(7z^f>-*iEF@C?J36z73YvV|>;qXp zDi+U}qHWSMzx|k%cCerNH~-7a%Khg?t=|Y6bZy^$Y!cb2CpDtNbvftjj}};tkkPgX z{j3+J1h^6~14mZ{|7~ZxN%UWhy>5_3X$bYW4TZec zq10<=sNae}p{Q$p);-#Y8f5mV{pwsRS*9k8=%UOjY)6^cIGVX)Nh95;Zo7Eqlp#qG zjmBNE9_oC>RLN~dMf}!1CH8_*-2dr>yX?wCf2~CXb*)pxC=#MuO2B2l8vU6rjS0;! z?4?CZ>fX2=1jWQ)_#qSu6MDnf<;^gSj?l_#>#)t`U#7A4^gwS9Rm*UMrUGBNgizkD zUcqSDJ>G=vKTw(>A+TRWFTUa>rCoun=R0?%7BrTJvSV_3ZiEV7wi}SSn=I+(i1^ zr_V+|q?g5Sr?U|yEC64H&S~wvP%HWMQo2oyGhOua{(I-Xra_)<%1g@l~o#}p&D&7@Ey|tKD*zws%yQ3mlrfI{{06a#`WAtLyeC5&_?Bb6cE6l z@RpM=`L26J2-116+N-*$$bqq(3G@owQ3-e_VS3Nd4Q%bmLHH>6tsCYdg6DK2NYxM) z?X%3|rJr)fHMMq4S(qaVGo=77WXXtcyg<)4t|MVYID|_QtV*w;Hu+YmKO)*q?Eu@` zu-!;i;};X1g7&-V>ejDPB%1dd#|MW2_7PKsb&F12b^#O%YdCjdJsG=F)6GHyKAx93j+oJ0eY43Kvu2q#>X|^!$-sSLjVXD1;@cITj&zAA_YdT zby~t)1%iH!c||pKpk^)Ds1x?akU)Xjx&r6?Tfj0j5sklS2%svF6}>ix--w;U<5)PN zPa7JD%Z4}u=3>FuTEuyN8WAF0VCDHT$Ol2PU?>1Na3^YCKr2hk#U@T~) zd%luz62NntO+0L;t7v#%Ca;$%85t;7@}$Y|YgW2N8F}#O->$SE$E}S57jL*-z){;guyEhR72@K zYy2i|!8pxve}9w><}WBOxgOd_FncHm6s5)5{xrIg9IinUyzL{!CBw9OTN=>?WFu8M z-|g6y*j3lf0C?*FkYeiOpoO`@iS-IqD!~Xl;5N8EWUMvY>@D5~cohM(a7ZgHoA?f( z+x3AUF=aJs?m?n`bpfhs-Sk_`o-t+B2e&Svj17Og{b<|-Hu}B=(RURAtQYqN;GyRyvQTZihKj*1N31o;foXVWT{;?@Wsq*@foH|TB^u%Z9F5+($3s6Kjl4-ZVJbU3);~VM zPk8_n6~56b&6iVn)%&6Nv7n_3LFhTfCtN_JQ6+d7Y}J&SbVI;Y0F40XwE}HsSe^b^ zE53%A-A~`3jBkfT?F}ch<2Rn~-)|X8n9FImOz$Yy!N&EMzX+ko!Dl6A`?S+PqUQhg znLlRa>wYgbu?baIGWHFGaZ)=I=P9ww)UJ<^%YFE}aB-KOM3H<%sGE?=l<76O|KQ90 zi_rH>Aca9ts^Q>pMu3z_>!S0#Q>-7w#$_?H;L&i~(G+w|98V>fV>b`C2_f3+jX4%? z_^$nDFIwNB*q_zrW=E9Q?cIhxh<)*O;+ltm?GHY!9j=HHZ`%5K%1M4fB-=~E1M#v; zRBY6qcO8{lNkM7nzgkz>dCjp3=5Fq68 zce*hY%A`s);`*H&-@qIZ*NMK3&%dJ>UOpO> zE!6Im#4eYP0*5$RjV)IexbLP@S%Rf23?C`TNK9e8C$a42zUl}Zc^A1_Bv`chxCUCz z4{WZ9QZTQZW3H%2Gb3dbsf_Jr({7#C!Mqu^zGo-9r>eU%xeh)y6`Y>)mzR7VMxUJs zCSJ#kC$HyoWE_bZcoDg}Hkhmbt>SvNU7#!t`Hl(CyWJ@-&Ir6}vzRsSPQs19fLx|P zEDml;_3}`AiSi$ff~bRnWG`0ww};7yWH!EGY1!8FDGlVFMa$)dacW-fEG0=ky+?<# z)kFc<8D7=<^ReiWE8O9raJqUWX`nrW*|+#zk=e-7yZRpoY zWM@j|V^l>73}i215j^bZ3_tP8W6Ls*n?(Hk!eBZw(~TThw6o<3bmP49Ek#C^DLyWG z!IOg^9d6FmBCJE9u?Znp@F|i+(uT3`vr`KhRVDHHY0oU^jVz=7geeCq2iz(8ZuMe0 z|B6?DNDo@mvK-w;?ft0bl8v-@Jah9@36~kh^I=>$6#1hf!gVE5E;tBB;h?E6U>)f{ z{Zv(ek+Q|emXvRb8!fao`-<>OgD33P=lXWK5=(|gDPDh(@cIwX2)y^-xk~l(ww)TR zqS%G_%VS5zji^J@nRYtc@4p2ye1_p4$X*P8y^PIg=kVMfNCjrmf>M2r&@Z+|(__Su z)g_c4sq6Y8m}~vua8~5yX;iyN@g9R$W$$?JfKcHX}r%ImGTH2wimP+fRW|1cK4&aCC`TOZ)7?zbxsm zenvWqsM5UxAWRpc;S2BSV#7HNEY6FJ>Q+F^_}7!Q zSA#M*(>{V#fkXL&3S+gLCj{zXK{PX#Rq6k(Z%E}4`@UHLhQ4dInw@r$ANw{amu-wk zt;b{7Y%rIN^OFZ|Dg{#7=i5oGvP$j=3DxeiDHRzq0RVtt{8o5W75}+e{g>Lx%9jd< zZHiC2YNj3*HD*aGo8y{VNtY`!BMmBwmxN`Vd&NAjd2PJM)%13pYxP=;oH?4m9V;&% z1x376SOOO;Mc&wCyM72Dm_QT5ERdab3aK60CeG89Q|0RV(nbgYShWax+O=J-YIy~S zPBr&)kgR?h6IeZHsND56T~RAso_AqT54u-l793wn_`o_rX}5`HAyD&=MEvXCPMXHL zX&0Bmud2DyDO{kH5V8F+cLu}ob`8=v;Oh>}3@$~AsfL;E{rbCKud=s&#+*#elJPi@ zo@16qzOLqpZ1q_UEV&kZ2FxUeD*pk#+5BOS95Em;7W9#33}wmTz14gsToiRaX5CkC zkoV|VaSMyy)<=u4ya8s8c!-Q&fVR~8#PeY!DF~MaaKEIL(Uff+zkZJ90wJT32P2Xd z*jsGM{89;I_2bT}NcBpp6N2#{%l1~+Nffou8`PxIF)bK5cHO3Y@trzVP3=9-rx6|r z41JWl821wE&FpT7FMA%yi>#^eQyc}#GO9`yEgZQpTkt699V&ks2ufWfo4<8z-$ou2`=fMLC zquWhfny3r+2=6{xm9>6|zjO;{ZGGZrx5(jL_J(&q!KLWrV|CMCHQ+_SL#bc8pP*mx zMkS?Lwuuj&v6Q}jJLoO|{d`pB+o=-LJBu zpWL{Y4pWwKOHX(Xb8}Y{7KC??xaJl*rEmKBzKg%9~77SzmZPel|WhUw% ztLr?2;rB3KZCa8VH#}^^MLWC(scGo*(L_<;CA$l`dNswq_S>QO?1V?E^b=bqBpX!* z(pS|vUMc%PNR`#0A`nHgVL5rq^&m_&vB(_u(ItlVi>gtAku8y|)ojb%zWgsW6^L%! zr&h}i;1hn*M=8FQecztrENF95p6jR2%pfYUKOsb@bCE9*;>K6Z6JYcUCQo!gzddi| zq<9Ry5kAqvpO^&{I7a-G!k#uW=ct0Ls`8T>9V$dFNNqjH@#*?WO69)4R4i-PluIQC zf8+vZtlf7%YnvcVuwn+y`RQ?#C5qkXPd%K%*S3d+bvC~hc5GN@KRb{ny>(Y=#8S8& zdc^n6DK*}{KE)ZPfSrfcYu1$8Up4ycA2s^;=rA$*xo@kC#+N0$WDRYDb2Wp$bW+vf zm;vD~MKhZ*7YA8vxg=?fB?gvVjBTN56Yuf14Sm+3^Cg=;{ijU!I_SE->rUqBt>{&V znOQ$TbCalB#BGMHVk)4U_I7N&FN8^epTX7f! z?5$yXT$K))%6G=|3&l3B?)L-S{J2&a_60%z0pRC<{sprKk1a~Td-)tG$TV30t~VRA zQmVBwR!ug$smT~i{=6iWK2Uc54?uu@zJ{jNZEVlrXzH3YcamUKqb|tu@FgwDE*sjt zhnd_?^h4`hV>AD;hrj)+pO@kCJabm$pBTa4Y3T|1t?)U(PRp_Fx@|v%a;;MFIg-(# zR(pU$q$(Uea&2OI^7l4HE(hOQ2Q< zw}QosFFC6?n;Tzns2go?m>~nU-7nyFf907=Cs;m&ZJ6HWIZnrK*Be?y_34KdDH_+q zQnXN-2ob3$CnuM;X-^w|D(FbwcwX!qRDEhzA;G~cm%YkqEyz&fqCg?7wj{OP$0q)U z5faVc=*5?cT(6RA-=|*0D!2454vS9LkHqzdb>_EBQ28d4ki2-%Y?dH4=vdV<>6KU~ zTAk&AD{Al!v69nLnEc8=af9os9&%&jKI<9xL6Hv_7z)nV#BE()+ZCcYwe=3^J|6kfGCyOyo-Xpj40=CS}); zMkzNa^jxe1tkxCL^|g~-*AKa5F?BTk-En+BAOiQd>sy?y*Dio0AepE%UWT(v<%~K& zdQVH{Frj_UcD6;x4%8fx(%ZzF%k^T(Tt8*6>23`pcjMZZF68(THSFy80v2hLeq9(4 zetB$S&>EoHX;XPNFoCa3g?Bt5agvTprcey{eZ(E2L=p?bTOvl^`7UnC1sJd1qDQUV zM*i2T>ir+F4}>+t1k9eWQp`iw@$HuUO!<)?`cauh2I?BEj^`>}N1&E2N3F z#aPHVd-i9hp8im6&RI}Xcxe@frGvL%#qCykffN#a&J-_agf21pycw(JoKYgC6E$vBm3;x95?tXcW-t2}MRw*qNX7tc8VDf_fc>9*H9 z8ObUmUqfZKb7hGaeV(tmKOjBs#?ml5`me2*B(Azm`N|m*7XVSGak=Q7M*hxczEi8r z22;B|49iI?CO4F_rn}ZzO$6B&M_Miv>KgBy^rt7=%x;9X438hIK21J+rJr!E*`kyF zY~d!UCS-q}$%`;dS|R$zQ4hH?c3IgvP%Kz~qV{4~>l0z>EpWCY00FI8LyYMTG@TD4 z+XkePGJaInEJTuu^=#DK=(aQ8Q3QI-wX4}!c_P>PGbO%HJxDt^m_aa9`w2|2`WrMJ zBm}g1bVf~g{gN8!a2(7fNa@Xe-joTRM5GrTh+5w?uG=0R1=I&6UaK4uHRkh(9_^<8xHsiS znjlv+)(QLXE$(+xx^LGxhaXneUCKrX{Lq zzp&S=u)}|>C)JbRuwGrl{U<@TP!^N!e8{7N15GK4x^sl)e}Ej1E=nv_py3~J85eP_ zNbK{!UbZ7jX|n-e-s}px1tCGQ^%^xB&?kzV`(0!L*a=3?!N%^Bw;$egW9~Q*N@?76ex#FID%nL7U%;Q5E-tE&{To?Y0C&Ir zq(=DbVyo=lajF3ninEZk3l)MLivs26gczPs6CDi`uEDui+r}SbQg7YU@7yJ7b+~vMuTiTi6)KM{(hQm2%4UTFb z(8!5>>RXvIjAL8i*aPJy7!eray)RmAv)u|l54ydy11G8&!^(#DFRLo}tZT!M4LN8C zL;NN-Eb46U7%|R`%6>R_XIX;c-mhV-7w!Ua^$LAcI(8n&iTXH5L2^YNeqJRQau(p2 z-qQR@UXAbM6T#05n!9+Mu4d&wKne&6k?RV8PTY6CgQS{(kDO8E<6`_U;&$yFE4<*o z6wKje+Z7qorEML!5Z;@~{Z%}+io~cX?PAO-0GQ5iS^dvu|2rK7%xdPqv_0EOu{rVqBdhUg-ee_6eMZ%3jIeL1> zL(ZRE#Oyj~j6dOPr;IO>XRs~>c5@kp0|i#N1v;X-)Fghb9y-(Fu!3fr_ME@yFuUIh z8cZ7}i7ZnW2|2kT#>C3PJJxfn0|oW?0#zWw}(4oqm-xfq`4Q_nFr$4pQ}*1 z1Hs0w$2xK+ck;f7`*Z!o0r<1RJ}lSR^WAJyWf~a}D=|ZC_0cmj8k97l0ct%NWP@)MW)iW=nOAu!}^KA5fX#EtA<<6sHj>EDa3jfx*+ znqqP8>2fJ=4KGGnOS)_L7+Y(}QWH5|zbvkwpY-T5^1-&2_4Y_2WnUkUDhfynvK}T6=^5U#6 zswkp~q6Th57d0$J!LHv7MWfdflM2nONrTq>_r)X<`(ZTV5y8ukrpM>4KvN|kN?hIp zVSP#bm*q78+p~lt70Mq zcJw{GANsT~)KrIGEb&t0f1ALpK(#eQY@~-QxnqFJw7nKnb>=c;IRJ3x?w_D~CNmR_ zcyEb&uOi$fD|OSJ#@LJHG2-?I8gxDO!B4pwk4N@Hvf`!P%MW=Z8-@>_bbiMxg;B}B z{TJG5WBDK8trY?ruG`d4L0Jh=%xf4L>KD1Vyla?nH0jLPn4fHr8{&_8Z=Les7IjhW zalJ(me&nLASZKWmP&K=h-b%2SO#8>vR4aFbeU46eKyh_u$O>HM!cFkNnXOHV=-lU{ zrQSH43=X&0Klk+j*g(}brk zxQNiWL&@R0w-y!eGj1lAVhyKuK2|q!KWfs2s7aoe&ntt9#b;YiD6zJ|xQ3UZ1jf50q|5~IqI-leR-GXvuyq z3ui2=4lzgAa7|0b7|1m%f_$$>$pqUUJ8dXe%3NWIVOZL(#AqN&R&S-7YnDA6H@Q{7#$_QLVYvnA5a>wfAz^JwUWLl`aNLn6^}|ETzKF}zyka9zm2g> zcZ)V|1(yzT@=#F`$lt|1tXc_=i@N$KPCwj^+2@%J2a>1lgpa)f5*I9jn{MA~^Z^OZ z`8X+U;NR#@0pEc^P56I+WE2!7F|@QKihTLePhhnjH}1Gl3iu@uAn3IEuYuX%xpt+~ z;O^S8l;x>LM!d4v5@d5CE|o6c%$b>DVRK^oWX2u^89a(-oyF6h3?BR6DGPb*xK=Ne zAYruXEPK1A5NefY!;cwIEx2_Rh0b!!>Ev8$;$_}QXMQo?=hq3!g>ZcKqx&g$@F?@^!vUt9k8!PNH>jW=&*}G=a z|Jrk0q#mo%VYSh9yyaZ_jwU@$T=nS3uSd9r%$Y88U}Xgx+MWMv@us;jC`)Kih(6Eq zzNVh%@XGEN6t$QJjAIebf=x_s=pkx)vXKs^NWP81T`DdBYE-y1^6eS`wu zr?vdh|3NbWz_fq9Dr*mstay6;YaaXgb4r+edgyuiTNxr8m3H(-8@H<`D%4;Y`okm+VUD>lW>DPOBp=@{Qc8Cg!rN~O`J}jvF<=_s_o<%SiOrr(CO#X^3!qO zXa66b05O6S3?dv3Hx@9|F)a)31GMZ_-hDTVN$YS?U77l_$K!KX*Eqd(`u#r=k@J2VTl<5UCxkKgE;Jdu%R!j1qSuSaV#;6jl zDk1TTVr{LIONSv*W@VB!R!Iot<*|O(hL7(QmzJ1?RRaCPN}1dHk*zA~g+s~7+$^LS zOABZ>v(3|q<(2x=Fh2rz38|ow`T%BXD6_ns3aGJ=!{?3zgn6eXG`Pk*`kce0EFM5Q zK0E1Rnb7C#>1H4Mk5K8cdk7HM996kujDL(fEleKYJyjp~DI;jp-8~RBGxlq=7&jk@ z!Cw}v9%hUE(g=X1e~K;~7hy6i3!gRU_jyJ%#T{RP1Ux4=+h-4)ZX)QOks-KSZfEE+ zMHmJRgb^SimUaf8puSXZ*)_Dus+6(tZ7;6~fYOzA^na04n`;bKfc*6V8INv#3h8T~ z?RLW)bYlM^B)q=Gi_GL$U@PKnz9={oeN?KttmR}F>A2RAia9auTV?zY0Jh4R(;>_j z^#9QV0A6_vX6^*NPW=p?qXj;b*MH&4t}jx0@*zGE8?F!BM8tjB;hOb+8uxLLAE$|x zK+&8YKZGBq<=RviklYyCHr)xwhX6N@jbsr66O`!ux5X_`2lj{QM>^lc5;qARY!P5^ zy;oM$uYy(Y?y%2F;$DR;jt}aNGWtet;HE8>Nskt{4cIem3K-?U8-6Uk@xQ<_VDA4w z?X;fy66yzO9^(pqNBGpO^_dVMcM!kR<8dO7686$%xw*+TVyGRA0==tT^Ug|p`r@7c zCWOOySg?oP8la171n!BIa1m4AHsMoAbO+G~S`aw@m6An{IB(u)!B_Si&I655Mugs# zlL~3#`YNCogDb2^0N>2wX&RVfPNPof~#nk}km_zOB+eWX4*- z0$bxE(~J&}(8F6i8T1X>bwH_Gc_T$w&uWcJzA=Y&1i?3tJgk{*UMbuvVO7FBsa^?# zxl~Y5{9b(*uc8oN;fkBJsaK8FGC>9R4E%{&8x>->Qr;I4OE1pkH*#viDg?m0-3|{E zmmiar>5r8AtRwj1EB%A@{?;X&sF>M2A}Bk;Y*Dx1l7uV>W9~s$dRvbJLH(BArGc|J zf9J#37%Noxl8d>;o9|GHh37K#xI93W$Fs)Dwmi@JNA#ceXNwYMU$f(h(an7S(4Mqs z*WMO0dE}qo2m5NlIVW#kVgfnPlBlc`mH)ITK`JT26!G9QJf+KSV)1TsA_Oakp6FWy z#$X2u_OJ8#99@5zs@2GsE-_|`YVrH$US34?HW{E!5;B&14Y*;g-V%XAcjm_QAbX+c z1ZmLXYvA=J?*-Cct<(7}ufS(P*izkAxact|k6yZG>KFvN)OUtD<0iRgAw1p?ctwgs zaBS&syf@kTD3UCT8h}WahX9P+vqNV)z{JpzXw}QB`<7st!aJ>aj{?T7O+)*{dm2s1 zQpuLf4)@>zwYRKI32xoNX*0;xZ=Cumn{CerlqJIG38>zS4B^8#LH}OWoc;=4>SBO> zaAgQl-OiDm!$~ysH16C3o$T@9aULy$r$bQ@l+RbVg$cyV^i+ z(fqaxv^o1Vu99w#yGfRxLtaQS~tfvfN=6gd>wDC07gR&F(L#AIn z__zU8gtbO_?*L9-7B8kkFi{Wz-_gwgU!60J01|0VBczF%#_4Vz0zd%sKL}>_joC%e zYR_vGGm^Bh-Mw*Sc_l^fycFpfn*A9e(O$0ee%Icp=Y2~0^W|%f`+BTAJ`04F->s46 z<+QVu^=%?w(Pv3u1AK6))XEE$(TpP(Mc0p-1unbabt-XK&t;gRrTfa&C5Si@X7P41 zNVTG5dU+5!ngE2!L4zy7YM}V!$G;MAuAXu3gmL>CHhKf;m*bvGjeNru8J0R`RgO&= zOH7>&$2@7>T|5w!8`0L_3Iv`gTezf4RW^uHRa^*Y`6Y&*4vt6gO`kmzD>bOawi9 z$?%n+@i�?x_jS^if=;|0Uvh3^nBZVoRz0Le{(lbVFPid$on$)-)ZovS)(!*G}V> zf#Fvz`)|6W93;&jF4;4aSMmPkEM>V(ur# zFk#I{!X=nn>3 zFt$G|rMSXrF(zZxO+~6EGLwI+lr?zf%6@opQSsG*gvUb9eGC#aGZLG66EbF&u<&V~ z=}C94VUcGhJ<8POZBjCkjz2>#pYY`I;!CIN0rP|zU|Xud(o|t2YY5p=RhcP zK6?~ccB0@A;HbsR>KVSw(8A=1FQ|9f&HeLdo)cHF?u7b7Ple;x>4>3)yYA~Tle#)j z@@X#W@Zkz=qmx~FmeeudrGfWomp{Ez4~(WipV`t4-DqoFXEpt#FH6xj6cq9Be&w6e z|IJ=f=RumdKHJ+Lgk;MUfdm)utWE*!wEw3B!Ad8=1tunXXRK9s54}Qg$yqs!GSG{w z=Hb9>p6G(T8>ZPlu&VEWH}Mm|vRjY{L~6A704JHg6e;mF)Oc$8Y?1T{^#lJa?gPi) zIWD$7HHTAu3(nq_=(a73f=!iVK4TkOLO+Uezr%^y76F{;MJhes-NsY8W#dP`Dmx}< zqLc3k8VN;ecBpJhm!O!J-Rog;rv0MqTh&1-!KoLp&@QV9V)S!pz4*ry9RS}SCV%Xw zfRE%^Jy@|J3&!Y+2^wJ(SHe@Ei}jM{6DDAG z5Ne4#CHL|Q8WQO0h+hL3d^EK~}`8M>O4mE#R3I4Fa^s%FgyHbnc zz567r#F^2e4J>RopVY@CMF9`oOssW+ISSPb9b$1b@XF++2cG~O7VfoVGE*tv>yErmC@_5U)j0uUb}xNWBouQMQ)VP z@F&*bM>c7xG>2E^v}?yz6E8@s2w+{WnIuCJw~oIYoC*{C(ZA~=s)*c28@@rFe2nP> z_>`ZCKvE;={6GJ+mA+Dyq8%0HbbGl=Q-fRttl@wVkwjMu;5G ziR+QyU07|^pGIoD;fsB9E*nE-;+{~vD3gd|?QJ5>`(>K_F*^$r)#QguZSwaHd_T6| z(}e)(2&Pd#iKWz>LjRPq8Io=t4plBVTP2brL%Mq1CnVgbf7=lMWU>wkm_drk+~n(k zM}RfQnSijdCv2K(gG%f%X(XT1UP*=^INICSPWesa-;=o?nAa+Y+O_Q`IrN*zW|$y1HWV z-Gc}yk~F-GV3)@5@$CPqsvqg4r|DJ<`W?pQeR)o)mz&db?`T3nu`tZs$OL1!`%`njTt z*LcC{l8_&qR!2Vq3Mw*w$u3_(wtCOE1EXEsyEZAwu=kFX(ESk+t`bG~Z}I(hQ}yZZ zxv6AyrRl-bGks#y{0ile zri&l9lB-nY!y>H8ddG6hr2)=C2W+0k1v9Qb#)xcc91Hkz3J7u-EzK7sm+UDA{k;A0`4(#14WQ z$Y6u!gjh=F-~(xleF->1(9Mg88gECaqFT5+K*|%MZe|K7VdtKsX`R`g&m(G^7|_K0fcmFSx|rEPNG&4$gd zT%q_w{Z`=#P@w;e`E#C}m_h1nkB92NDz(FCaoTXO?G7u?j&@4UR*I&nzADT~i3Miz z*SYPl3SDkrj8Y5zQIu2R zK-zu*(3@pjVOwI(fOX;yGChYWYm2{fcP8g2G}xZ7HLqJY`M21V6oBu>O=Sp+0TmzF zc>3_#=$0MqSRYCBtSU^EaSxr{ON|&W4EOIf;DGzG$DuVcKlG?LaRxju5lu=~mE;$Syf z4Orz4VN&Eq$8KpQG~Tap4gZ$>vl#xbbX*E}>T;?07jA2v369cNUO)f3#^lmXr8I1I zw?!ks_@-+!S+Kw;|2*NlSPC)_e0yRg3Eos!Dwkocd#FWOR-{ zR4tyVfs^2(QP<3$4(3vx8;~|0!HYeVi6zFjw3!Xnmy?x9ik=Aai=;2iHI|-zhsl zafLm`#(%#uQeBw4AgEaQEii1bKcF7~RdH?Nes$m0BFdaR9MOD31_rqP8ad#8myVU2rv zgst=P05*j8tHT}eb1ER=7rtQ{%~_SNU(Bk53}t{OQyEf?=)XP$;fWTTkxeSjJ-^=X z7CVqpiRx=CgE=@!Z2?SPGKaZ;#muCWqP}nZ9d+}ciD!&$b0>xgar+YBr#sck$pwy0 z4_l6F6~CCz?`SA%ZnM+=$|M@5HJ3S=u*&87+>9|Weu^M@Y>p$CN%!c;x`9m|zS=dx zMWHx)dTQWY$>41k^&W4Cy`)3D^7*%>_gT)Xt1YC>&x;>{Lu zzDX|PcLZmU&4xdi{JK>0Nu}s|tU9HYtiDN5Wrs}R5B)Szw1PnX5(n3{a{mAmHCg;N z+I{AQJn>%1h~gQmOMrtHFYXmIplkB*V>tH;i!CDGTXJmi=FE1c?{fgJN6%!y;jsO?~*vQ$WrP^ z;bMeJOR(pl^cf#_rgL7Bigt?Msm$-W?;i+$H*4PwwMpZWc`r1EZ!p_N>LZoFA2R|8 zIT-|kr*H>6bN6nKtJrv#PPWwaySQ&`t|JbDHU)>V1EC!VJ?rw)#_^7wbYxQ)jv*4G z{{Rul{#iBZAG0sTtux^-j;^QHW@BY_ZXljpc+7@Bm=)t7W4Sz^mx0ZBwP`nYhoRNr=d!V?3lyRO% zu?K<=B9hllRJoE_lshg8dvnt@!(h2t?2!vW82OV21G(;Mv*{0aB(b<;ibX2Lct4+N z+*pdaEHlp@wAnYRy7HhdK?AR~78TBF<3o-+bcY1G;X@Y#KVPjn(?py1g|Mp3FiT*L zI*QY{3bUk-3}szFEaQ-W4{Efq!!u#yDYpkGaz7(TcP#ubw>G{#(v^TO=Qde+>WyC! z{?*VtpR|{cwkRX}Ky~%zI=L8TpiJ$EsjYeYjQ`uT3_Bq4%8SN5-Dx%$DGUt zILW~6-n~nR&1-g%%k*~Z+LB9FjgXOrEwuOTTT#Os;oK52(;SS`{{XX9#A$$`P6p%F zj&WF_6dCf!J3^dwtMMX7Gk)+F#_%)S*Yl{Pw+TNymRgi5ip+_gv+Ouxp ziqc0TNEoO&%u6;rMYtOac7+vbOUtx~h=Y^O-c(IlU4&uQl^lrJ?@-!Uf{X ztvcaeD~oGjtkQGyNq|m!jiml!zJc(?uZg@nugj=Or;@Rd$7&KcJ7lRG0y3i?g>pX? zd?h!DC!14vL|3!@0o&!WoQ4P7llAA; zz1zc=mOdNs&apf;;V&;0ZTC395hhBif$m8syEoGxF8KRJyua3NC7oI|X2==F&iKc# zt$mgfq^s6$Ukp{3>U`yR`zn6!?Vj22qxQ?V@ZGJOYnCmq&ubt-Ajg{uc64?)47qK& zTn}Sim&DH$cw@%UTx&W`sdXjA!ugAFEyJ_O{m_!%D-PiP74fw3e`1)PJjU#~BzkoG zfBN;%{4nvwrirV~7OZa9MYv2#wsE9|WXRh4UycSx7(CHeE1;@zXi7{&I1`_DxykC^gv&m32-{5SCmYrYlJq>e)E3}QJZb=p~m zM<9QVct?(6v(~Tf?(~bpeQIO_bc$n@c;j-CNZ@@1dvC(O4^83!00vr+#^EkNkqY4T z87JsZPo;bCUggg+tgj}z9e>%u5Aw4w8PC?LOA`=#4D8Q(xe;b$^Rh5=$ERv*TgfW2 zta$0<>P>1av3cio~%^xHE^{%eD zkBKK9554Cc$Itu?X+4II4z#j&S4@z---?wim=XZ!xj*4oY?o@4!RM$w#aoInRFV!z zb4FK+RijEw$+y*}RD9)AA-ew|HdO&C>n9GvlyL{X}YmFww1T!g2ZS0||Gc%_Oz z^pL#el#mCYt1JSz#(In~t2XEdBw+QR482$9|wPD{{RkrC(tddbn7(V8V&Qhg6_k)_pd(v zn|>I0Z}w>Te{7n~%KreuM}HdJUMeAyW@0!{stLg8J!{>(Kk+BSz9%LvJ5X6B1MWIB zZO2>&12x8yt1HW8vONj8Q&xw~{{USLl(k4fV5l+2-R)V|a}P9tp^vHQT9V2d79%`& z=~!~#LuUk+6CI#(3v@NKqoIT@-O5^&5(2DCmd6UC{A-T!2AKEoN+pc+A%Ot#TyKs( zCwQ|_y188gOo?sd`BHnW#hIP$o~L%V+Yro z^Jb#Q6mJIRn&kIj_3>PvU)UT`u!W*Q`W$*728FtwAw`&IWRGkA899zD4oQwzj&^xo?rt z`8mK04`1`??_1$3&JU5j3B}=~D0@q4j4y;^hyjt?Uf3#d@I02>Y?gfO5Fw3_|~NHq$*b=DF-}%TBjr`+(*L_Ngk8|pY~OD+yGLisTtO&+b&))uWsQuRV?aRM#~o{Lz@bNtG+&n=>1p1Y+z&+YoLTWj>tJMT=RLNH$%z%) z1O*4Ut*;rU{8X2Rzsdgqpo+za9pQ0>Z))f>C7v8Nm>ZzL+;S?c`?fO>thnh`U6=q6 zW<2LOrj-W@K->>X0Ky25FAwDI=udjH3Wwbnbm$1H_cpPDtW@*HJ5%k|QT}N1qoJS% zLGu<8HVGVL@tVN+fvz`)JTHHL9v0yf%89yRo1y$UKZSJ0%Op1qft4n_ul9|;79JL~ zING8~WtS)AA!8#a*Y6scXo`xvNb;=;<5BT#)yIT9DP=9bvvCe()Fxa-Zio1fa@aqa zABVPhJN9fI3b8ZW>J6)F{!v7|)D*g*Jd=QOa(eU73bFe)co=wN!Vqe=NLN+WktUOQ z$wbG>zn3T6n)gdq2OTTTvYXWQIh{43@_&ea5BSGS){LG_lWCHI(#2$^6cQ7X%DnB) zPfyak{{U3@RpKFaBw|HNRwZPLK-lM|2|4_YefaRC$%jzO=xYO6&}?o3qr!(L10t!@ zYi3Mp#qN*J9}|2e*JWv~ZPIJRbSpBKGA_*VhHpIX#bybg$XA z70@J(V-qk>-LH}c0qj>C8u?S>AHqxT2wgSKBPk&x}rG|SGU$;IT*Q|VB;mtc*)1?zwY8KJmLg4jBP{aA+zYn}oq{E?W zlEB|Dmd9vcLtm{Qu_ms%@9e?gsQ~8I8EnZv^v+fv%N6dy-&5skN0qeCT7i|=sRd4W z6=`BtC#M6gEY_ikBO|9ugdZYKauu=#YGf;nWG^SuqaaCz7$A-PYWKPG0*+`uPFftB%C))S3LeBXzW36ZdNRj-yoi9Na8NX z9A}|DKMJ`LZi}2b2l#p#mPIQV1LYuc0H`Rgs_0cVsn0p?1zJGT5&`$eYObnUWf&v? zGtX+#Y>bR(C{34#h-C}EvW>2xPmDx;jl_i{VGI|eA zdRMtX2JU)v9P^s^Q})pDmEVj$C&%G?Ml#sx%BslB3K>YtAH%2DH5W9Bx#9i`xsOb^ zB_mdy*zA=)_I(M@HRv<=eY{C6vOJe_-z=flFrkW(>4JY>=~x~O@X7xGgp$)m(=Fdn z)ow=F8F&kmjy*oL`XBI5_Fc2^#+7L{qZ(dax`&jy{nOWIIqCGSO11et)w$}>!*ecq zXpfnEHTyc)&uF&tTHTbLM%QEoqi%QrbsZ12az7CN0B64uXw1oI<(GEz4ob6w)8)zO z>0hXDcv{O%vNo|=q-l<+^5^gZuyv0FSl-C8O9(qKLT8NjKDET_RgR~l8Z;-N`9A|| zIxWDr)wEmojy40#hDS|+bjSz!*5;#RHC-Bcbo-~ei4<&z9u!r{CJWm`O=O=N8)m#TG+q&Zv#eo;)C#mPID%*u1F-#v%T17F+NF$NYBN#M`xlzm_ zaT>Fi8Qj>&^vzkfh6{MXX$h7=g~0p2{d%z#q5?}P$s7uSEv7dtU*=r>>~la|xoZ;c zWJTNl(HxvrsG!^l8;{iVsO`%$mDz$aGQ*Sftj`x~r@`J2*EN}A60VzLJ?6vrPnQ{N z6X;0&Xd`ps-`hh~)b$UK7V$KT2AQSWMQsU5OqeV;$i-KoC4f2p=+A2M-AY|A!bv^h zzm8bsV9yPtjve#r1~3PpHGkorv#M(Po~Pp<5j6UX-m|l|@w}2rV}si#fsx0hb6zI3 z)BHuRv4$P-yBsSs0zPc_T<7bW=vGeB*&C$nk}qnWE?Yf+ON&RaX>|z(`zfC#6Do5s z1ouqf^#^u&70YWr9M?6ATdhuMMxiWGG|dc~o-#q?5uccW*zv*5dS;p6R=luXV$e?4 zu_^LaL%LROK@041N9Xmd?FMU|D_gjiX@!gY4yq#$}Ri(nb_vS3k%8)(=kEJoK&t$HjI!7uv4wtPSPl zPdj+=EPO&8>K9c|5Cm$h@(M-+3;e zi2|JCmD+K~-S1yvTw9C-fDUtp?O&cBvCoNYo8pd^CbCqY?IJkhlZGnbsBn1smA0Ok zA&9Tho06otIpYT-wRm+Eq|r>tGl}JN-Sa6KUqeiiC3jXVLm}O@UjY3@TzJwcRgOVC zZpR1GowZS)D0gF)1Fd8tn;@Bn zE|q0GO)}2qgFnd2#uwhZ+t3QjZt%QH>m#6D-ed4LbjCZ=<9LQLt+`3#9R_Ok%Sk1x zDfvqDB!ix6x>~zOmTpdY^~EdP0Ki1bzFXnGW+HwDYEA zk3yn)(w>&?4~;lNG(P+``NNQv;Za9^ZEuJbpsB?*e#!(^S8Q zPqR-d)*-Sm>NjC{82-On`m^De!)WxII4*97&w^GUJ9Gs8AI`reuPXVrGEt}B?nm8T zj$MU|p8o)wJda2HoereQE~hKa3by50a>xGqB%jpRp~LW-OtgVxTXfu@D0Ue*_pe}* z6bX%>0a+K0k>qaY+P!b=S~Mf?JHIo;{?n^j*()Q*uRIZFV;ry;5rUtTfxsOx&3UJa z{uo&5O*Ud!_&bg|pYZt1}Q`#0{M#TvZo@;*WF zN5Ty@)m~H*G?>7Nh}bwhjxs+CSIi#~{2wK&Pa>+}@(EM`fuD1l{Sfh$tZ`b;6Dqi7 zz~`v+ub4h8cuvax37_N{CxCee*1fC^c}7-Z#8Hh%-5(10r^AsX?CB?%!;W7k@~mKy zTSbtbTx%H$tT|@SB>w=PO78w3XtG&eIt3uFUfHiX)SzvJS35@qvtMlo%#%Jow0)eJ zV@TCj*5*>hLd*apuQl|?!KI!*0;)TiV2(rNpG7@D&szC8fkjQsSdIYiUrYYa*E3)E zFUeQ)O32ae^E0###15T!{{ZV(Qg=rpeHrO80J5?+a)1!W_<^Y2^qF0kX$*1tRi%O2 z7k1h}8*)xC2U>xwoh^bO&PGWzv>3x7DH|_4KJuSa-kM_)$P=757-Qa<3~q?3sFLG*^miboSGPj7E)Bl3x=0D#yH}?O}}EH{{R^0;hx{TyW{@eWUtJ}wp(>c!4S3y zJBBm(_OH`V*tNI*&b}Hy^wRJD07_)6YkVSSxY0!w#zHMQ#@akaB%`inKEx+z>g(u6~q331lC{!_$hHV|=$5HGySm zt(tIl$k8z$d3uj}dc-zk0Fl`B&#hT2$3HRmq!{BP9;8qN3Y%EuWQw1d)8tXPjsQNi z^@uSHbI)qZ@z$(7GvMuCQ)7>^+dGbWk}wC?nwdK*l@)hmwJ87^aPk^LOpaql_+pK9!TF&n@?gFSRSN#hh;> z?0N|fSm&pvE8M?e4KZ|Y26(H*QxEj5XHhJ&Fz3r&gFjMh=jzW}zQ5PxeMJgQN8RcD zerMRnLeR9R&dWP?oc-xt14zfzvEwxi>?Frz|3YjhL zrkeLtL=p=tSRQ%aHsCsi2P1X?9Y%ezUU%Rh+JnLW022I2+J2FDG&fB-wl=p&(M!KL z0EPqR$iV`s)M;HU0yJBCy-%hWQ%S8`Z>BL`NAX|cR2~)6q(dO{M+&*>PfGP`4IWD< z%FJ`PbnGkTpNrlVxbbJiL1_|~w}crA7USjZS5|URHNwIUZS+S~;O#>1#CF!x$TmjG zT(LPg_O8cLxYTXn%r?bs)j?7L?fG`c=~$@uUK4FD8$Ax=QIhFU#PP;Oq*>=PN&yI{ zJ7AOBn)%=MocPc2f5AR8v(a=Y4!K~^X5#Nm(Jo`Rh^t^Ak@B+V1+oAbz&*g?jXBLe zSFyCJLNZrdp3~w>{{T1{9yB)rPD#cJo-lold^Pd!!%L_5rtiv!%e1)5g&mJ^R(vz@ z@5T~%q6<5_8_A^H14JS@&wQ_^U!`_`8+;wC-q>2|*A^{n11TUsUU~0XE_yW*pHtCF zooY{z`0K?wvq+Y3g4^Ol8*V3@6aIf1?tf>0h!T7+_?w|?)0h6uGX0+Q2l3mu+T3@> zbM+O${7ci{OV%QkWJbU?eaBk8;rnE|wNEufhmcrs!yx{BjeRU6loMMY7gn29We3px zu+vmr={BwzWIj@z%gAAl7<&!f_fa!N? zcp;+U3Hq)&*RtF~u@cS7(HOJ@Lnl@i2!jCCU;C%E*h^B^-Y zTxZaBs63Js^Rb6Ke=4CE(p#&c4x|8j9)Hg@t>9?3_|HctpY)`tz}(x>1Z!w*$EGl7Gcdc-iTmaMP=vA ziQ+Dij&lsQ!VE*iH zKX;BP<8PKSPVahbkYJW4jB`wa>J&g3iyuG^XaYhus2ffVc|XTFY@~fE%JMdn8Jif+ zGnY_7_C3XWB5jd2sRtGF*X=*4jUU8b7?roi&$$Z_r8XA%zfze#l@s_`tu1Dcd(m!C z>DH?O0yI?vXy^d0qT26n-c5PGgs1-iiFJr4tVz)Hr{G0J+rq}I>8!H~(p60(>{{Ud? zL2vsfcpr0T%}bd<&VKd7pF#e6*S|?xDIXt*YE>IYxU!wjszKw|r6-U&769YDEcVFm z!)Pksc;=O$-n^1H>06wod2OAXDwGEuJ5x=w#8f#MBRzPl4FL)cdH1TaBl&sn?0V1x zz$EZj1o7=rO&%GtMh8k%Ir*{p8kDb?3Bbp_0B8JX8Stlu0mcgv{{WE1c{DHr2JCWBE3Ibrm`ug=(J9z6J=rfDz@(7ekMf&4K72OnOw&n9-#j?DWT z_AU4esI`jt(^7@}`^WPmdB6lGZKJ>c0AHUIsX8bZSU=0p(;j}BJ#&v`V3<=<6pCPi5tYe1WRd3wcec}h!A-R z#sT*0`d6)sg6e)!pd4)@jyu&yW0p$Hoi{oIv;v)dKN^ir;&x#0bK8%lO$=FMf-p`o zp7e->%*UrV`ii1J;{yy=1E4)ArZVTZ*V?90g$1yE1w25YoP*fVBewW?7+(f>r~!en zj=cW>t2M>L0V|Groadj$yN?0c2xzGa!DQO07a5fm*(5p*PZ^;jEnm|c>Fxe3ci&jVcR$? zND4UhI2Gvz;b4?`ai$xoB-e?4*+1Ghp9OU&En`)P%@f=dWd~qjR~hS;0C7!d#+A>3 zd>gI*0L3>Iosny1Rw(i`tbEhlft+WYlh^<~E7-mZd^eNF-Y|mLMzdMO;7H1#7ss!D zf31AI3(aGF3|7wKDact63>EpgTz_8m`k(s|_ysiY4%^?{LL{0%3ppGE{yzTIo;LBa zPvSjn8jHN-z7w?Z7wn&A{vKPe562yzsTq!Tw@e_MkGz5KN)n`v!`tg#AMqdddz$cE zl+oJBkxBa|nQZK(k49#dRddf!Gw)xZ=r(`{r%KM%?4X_^&lqAj>0GkIsHEccHKmW6 zlZ^FD{8aHb!<|DY53H_TAY7n4CCL;EZG* z-7EF);|IeX7sSR_n#K>b5zDlFeLi9H56>KQua3SVd;qkvyPDud3dxc~DQ73!7$4WI zT`Y8{OH;a7IMd&4b zS*~U(A}uOlMh9$n`kK(Uk*!6{Qmm8SM4*Ld8*}N5@CO||E9$TKQ(9H1++aqSmyqFl z1KPe^_>+^s1RPc?DihekFZKShgmdriVwZ2mZCEb(k z2pkVzPAl}5@Sp__#RY${c7vOyEa4I@=+dGDcnXfGtlu?<4-VTDIkvj08W)4 zu#(;&5a4uO-81W&xR%NnfCz3*3BW#}S6h(ED+F@GB9sLf6?J9KMOBK!%Yh?CF~peK zJ7TxRv0x5FY6lqZYP6OnRVu-mvye}J{{5Y@BqsKaR1hS|=rD3|*R6J*3Ys~5 zWn&zWJmVPqOt}HF4mT;!1nuM=E1VXyHKdTo0}~)nSdMtf{(s80{2>+nuA^%5vGPOh zXXgv-r@zzdUVbxLQnzEKhLsWY=j^?sCabRA-po=~fxNsSET{)zp8mg=YWm(Qke~oC z0PSBh{>b1R16sOfEi9L;8bkbDYv|bHBj)UDR65s72=w`*87*;_j8a(YWr$2v`>)4y-X{JUEgpy_fwHx_4_sW z#VuCrM3-Vt8_kU10_u8#d*Ji<*MZ$BM=cS?c`N-zb>9aqZ?#Vz>5Q(zK6ed7X4V$GU~Yr3hHdDD>}9C9&GeAuh!8k=r$U$a~E)JBL;dIox<7>OE>H zCuIOfATnbsxL^@eb3&8F`_%}cKp4r!DUn*0W@93hA9tShJ0y_Ji2-fnziN8h#!)~3 z5PS5`y;a0Pa^Gu-W0nJgIR}ySuhM_mwk3!5b@0+JK_%ZFpXoAjU!2VgIUpWJ0VMSm z`a$~~fInx?4S)av?z(^1#FdRl?$}a2s){JCVgkAU039iB3|#@&DgOYWis&l?$2k80 zglgoFIArVo_@wp&%pg}-!5KX8D#|8uTN{l*3XQvgCnxUu3Yr2zZp z+)qQm?@1B`Y#)#xL&2$<5s@KZom8${t|^cpmT$TkDEr=@N-PA?Dzct~jxsCBKWe>k zbdQD6+J_4+rKmvys64W(Z(;ucj)C~su)_f-oE+E6zqbd7#g+d6g{+6o_Es|$CxXm! zGCJ@hADwdICCdhN;iJt_A2xWp_~?EF*KZg7ZQ{x|cO{O%KU({j;6K3?wf&s*Ee>m| zohst)$z*x$vF0xEoQ#4q&VMTS!$I(Q_><$$0Qf`wWuBp_Tm7)8I50*UX^%hb#7E;_ zsIbhQTE!BG<3IwU@DvV%@UI>e)kk?BMLEh4N+*PPOZHdOJPoAl)>hi?x2augb4PJ^ zs!J-vdLA|nAD3{LXz;)uJA>;|{2Kj`{0Z=fRXV1hqel0^%*#FG?{_GWoR{3^0OXU9 zGw)vKcXbt&xsp~20M9kVT6o=copMWSY1JY{JN|0kR)wP9$i@+!OUW;p)L&k-i6-Be zDCu7^{6qMUrFcWciFtE8amysaHdf&Ke>(SVPsjRShplf>!$~40;~*JOG3#HP-w-}1 zcw^#+#ffCrE#(>|t2&2Mu(<~r?DX(aij{G!vZ*~6w1pO88j-hMfEgBi^woPuz z8Co{a4)dJ&$PHTC`Xh%N6d*5ck!(J;ti-lLW-Hj*=`PIT&fyBx*Og*-9g^=U0Mn|PL&^c9EH*#CqAJcARlp@`CxtBRq^&#syZ5O9niUayYFI3J>_K^oIT)w68w(oWX${W1ijXU&3go z#hN>J7Ym*!Ta50!SXAq`OVFLUKkyM*D;owQDhE-;YMSN%hbsUkFP zyK<+T9&=8LG$ax}U^d{4RB@q*XKqip;;lqda(AaArYHif>q}!}b2JF8B1G(|<4ta7!*(`qjzsu^OIDOxrR+ezxA z9Gq5%ia%+)tx_A$_(#4J+UvG(DRq|m#c;rPP#2PW4DL0>2g>!r>$tG$B&7B1EtgL>@^F^%{KN1HuhSYmT0!N4%3X0$i;8X zChTME;T6n&x?K3$*2PjYDvvEbV#gTwK9$9I$KywY^gxZOc!tK&NdEwq(t-7_$!Gnj zynn4+-br_?Nf()vXxWT4?B#@D)?(@B19^#oCw8hbUAAUtj)o-v-J@kzo@ zaObDIe-rdS;wQ#$g*WxC?+|LboH9##5Ca{I87m%rUP7k|Fnqk8!n@Ddw?NdqSNl_ZG#097`zEF@=PQyU zh81UaKG*<#NUqzpYaVQ22`M=rw7x<{Sm5*Cpqeem(pO1QS01$vUsj>U89CYbX{JvkI z^`HuW7l-^)J{lO$Cxib0T*Y~E#NjeA*R^_|#o$kdJU7W4k&*uZT*Y~mEb=iCgO2;Z zrE|~XHjczX8P%5!pKp57vrrHNoQ|aRH4<94p(J!Cy;wiHIRF(=ijjrH8_?~;XE+r- zl7#?}TWIboJ49TDOpd*3&)PoE9E{k?DQp4B#Y-t4Ab#7vCv$bDSuBkjsFEdKgSVL3 z_Rc@xCca+%l&lWD`$KqcGPzlTm7tct1Vw%ogQyJ?JZ%pw}c#-CVb5^ zxBDZ^1D?68PuM3wT}$?eOQ%pqnP)5TGxL?l;f(&Z$yM^woANzOG;da%Uvu=sTlkly z_!ixvXlK-Q0=w42$|jajy@?7A0qtH}sD9a38b!mTpAPlyiWt0?F*Uj%2Y^_i9PwV4 z;(r%u9sts$y^;{K$@{?^U@Ok}9a!LFrdf^v>Uggb@i*;z;R`4(V%2d=~V~WmoX4_6SI-y3C6l9(5dH0UIc?XALmg+_l%8|3A0F1E} z^IoU%cjIToOVbyI^kHLY9F6|~XB%;zIb-_QH{xF$-A(ZiP&%A~TU!DnUp<&a(lcOg zz$YHS5_$klcm6r}(%%UDC24hkpm?8Cn*Jq{*uyJYLgARMRyb9>um}edHtZ4CG_dfS z)kQn^FBLj*_@vdl7OiZ)EG?&(tm;}^48sO79`#}FF~RH5*OvT7_*-|bi5B+ATWT9~ z=0TT+RXx?eq2y6v`$p?``h*+wO>Q$e`E9O&xl#{c`$Gf%_I|bPJ{$2oUMjSO4YZL? z0e>puGK`0~?oa4F%@gOO?R)yN@fA}ZG9v_zX;qJV;UbAY(C31@7kR1u& zeKU+6)#&=Qnz)8o8+=9)CLKX?nCIAm*K+g6Ada0^?P1}Ors;ZCvm7B&W@zOqIofN0 z@J*JrscLapHl=4{;rSjoe9QFT0G0EwjC{+U4+LX1>(Z;uPo3y^HK=mcDIoe7Do(s9Grlp{{UL~KlUxtB^u9)UgjHEu3@?IWR4I( zMp+qHj=33JSJ&ucEKnv_)6%;jc{Ma-5JE!i!N~4vacm*OuTnUvp;RfrIrgVWjOS_O zV;HRrN^&7qIN`kwBNhN;a!)3u1Rjl?5)D2`_bRc$z|KMGKplsG6psgZr#ynEkNak8 zj)u!*;^el_6KFxx>T9&{GAejC#XCkmMm(STW^0wQod6BHJutqew0j{T%@~Jk75T`> z$51M~pDGi^Gv2f$8@F|Q`t=n_!y)U&dJ)YchH_9I03+&YBK_ormvS-c-n5YgVe*`A zB;)#1)OlnKa(m{0CRmXG$jInNt$6qCSK<5pci{g3h@-KJ;zI-rcbjOpl@Ye@o6vMQ z?Y6y)Vc$5x0|(N%9a~z~wBLwYWxbu`kEOkwtv;8KV!O)_!GRo{00Hgzn#Qe9W|KV} z1`*>bxF>5S{^Rm0&RI15Udrjw3|?s9CNg@QW3Q!tzkbRLQ{nENERH_V@u_Ig{IT#j z`uh8t{M)tgWxtF*H9v&Sqv){TYqCWOa80mj56V5jHTtjc>%eyZ01kXNYo*#{8-%#FOk5K>F9) zlD_PKQ|0gLUgZ8Je3s(NC?}yFq;#rxkjE(pamtc%y=ug4BZ!Zbp7`!68m1+QXS7cfN{-ey}WFye6>RyO8QhX19P&WpHDPk`XWOBm3*HR2U-(LN z_wKGw{yNq1hwUDp@qavNwC!fR3VG-KRCV^ZgMl6>vC04o9COdzHSv$_8*eLockzp0 zZEN5G&N2I>u8LX-Zh3Te?jkrF(MLRBlTDV~msDNrybOi*^sC-eLZR}cft)w^(=J=c z0sjDq4a&>gn%?Z7g^LG-D8iBQ(z^o-D&RS8xg_nUMj~06_GRB3ukmr-pK!?%5~$gH z5?FLJfOW2*u^7}iiFcJ&>PH{rU1hc1?!*>ysexI1#O6TU4DM0Rdh&g}tBWJ-&Wb|> zZjuZDN$FNBQ^duQMehJGj3azp~`PR`150EKdK z&THn)XZD@B@l>~_(^zY%ky>M?=vqr^CJ6f(=H9WR6Ss`uXRbyovC<9%k0@W!Ecyz)Qaq^{80w2YPSmi04sXe=Suu*S^Qgf zWWr%}Y}lSDExyk(9=K@3x|4&Qp|i(I`yb&n&*I++Lw6K~qj>jm>x>$VO&Zi1_PtKp zYJ}mK8TSf3!Eodyfd;-D%eEi-cl2 z^d7bIjh?Bfc-K+HiF2r2K4dobk?(LlSmXsBtCGz01A9X9+CS;_!BY}j^s~jtJy@M z(2s6*pUS??)UK|y`=*TN2kw#Hyw7Ohk@Rq<8Qn488@?(X8$qASZ=8&Equ}>|8&dFO zx7X6jZ*@q^iQ#gu3ZJ{Tw;Xk^4*0)&bE?Y(5oMZL(j{KMGY|*!uKVJz?LVh}&)yr* zygi~=9}@Vg?j%clD2X9Jz}~=QlE)!ba&T!V?z$T=koj6cE|QYv+y;S zh&3Be5o%=@o@Q?PapH{ZI zy3}sgYobgk7N}o<3jh^(0~PDWGK1!XtV6<5l5oV=gK6~FU%*cQ{?1q54>hIL@1}d3 zfHsoNxPjlTeTCp#^uN%8K*wxoHz7INJ-w^*pH=;%zAN|%V28!grTwJdV#fDrwnhlW zT&oOj0D?IO>t90t%Ad3pUM1uC;g+053O-hlw$drwA++9VtmEp2O~};yS6EQ9v6-6!?9B} z$la5IQAY3TKPr>r3~3Z`LAwQ{AY}Exs=f#hZfCe)Q7xl$yFD3((fxlfYWG+0kCCgb za*v2E&ECIral4Z{bM?kQm43#4$o@JWKKK#g=_O^B;?~v}T*vIV9CqbcW7@wNC1X7E zw>jJ!8R^IW0It7AKj4|ZHxp>uw}qsbdG^X~BaDtp77Q?b0cPXgx>lAv`TN&r+4pgB z${z#Yty5Cbs{k@j1bSA*?&e&a5`QCE?Es7hP@|gM<|r^+spUpJI##!Z7iWqzk{I)H zoK+7o8b(~MRB{`xD@(#^zwndkWO4qGn8Etcw+41zDmd4!4tV*0^buKYB#SC4s47kv zp4G47Vn5*^y6cb>`+d<_d$Mpx<6Q&`a^fUBW&J6(_U>(&$qq(X5!h5WnU|A-7q2{; zxoa?6QWZ`J!TL}HY~4!t=nW)MklXr>nDnP8IXL4ZfNAh6BN2de#!saHSXEa|&GPY& zO5?7y>wOy2R+cq}3++M&jne}UBC7;Gryw3Hv02q}3Fpw(2a0qi)M07T)vpSXAdV6Q zs_W3MNC)Yf=dBjwbhbM%)j1oBc1-Y(1ZmKCH^;sz@Llr9ZD+0O68MM1(oe)!OK<~S z+MzrdW1Dkq>QYd^5Dq#Wf8h%oS;m_@x=gYRJXX<>6Z;e=Zhi18zW&G3d|{v_ovmq> zxAs$oX)P~dSrjnnNF#;^p&X9Jxm|bQ&Y7b@CC#72pBQ*b#T1hUo2#*n7pV#+^EUn! z=W-_bne9StB$xH~T=98-Wvk1LMYWxO#Ijr2S_5%4#JeGi6j74Q-GBqD918Tm+27z! zh2mcqT>MYe^r1bYTCSbpTWk2qFzM-#ZrL1vteuNE$jCyyH*tsX>fgb?68v-hnGF6Q z_<}5C5=(vKEm`ht)yE*EqJ@dvU=UeI9eUT-b|}b8HZT*CI2Cl@o4O*kN|8-S{E+>! z{tH-WUmq@R?CfIGbZtqaMv?^E6jvELaykv;KG_)WT0RN*RjBxXKzZ!6jW<(A1UPuq zNZINMBcGwKt-d#SX2Vvx)_=4#yIoe+_7_Q@yHLpJ26-P*)O5#M`F{5RBthH0#=ao< zQ?A3|t4rH^b&?S*7QP^h?a+wN04>C9lL74^e0tQ$&RQq2ykQu=YhLG__=n)Ph_&e? zTR#UyVHi0wDO6GKkbjV_S6=vcKZCp}b#15#TH{xmD-{lYUnw1CxNHyM0U}JE^8sH_ zUVK&fp4uX5DeEbgnp(6u=#b2WhXjf8dng4aKeJ zjXYsIdz#)DbbEOS=j!N8QM2xkN%6VG!m3U zfOGV(O8Ca+KMiUAx=(6xl!BqS z1F)!LkBm1=kCYmnagYj*dJ|Ak^>WA;cew3}k6UH4@b;rSI8_$!x!aTAix)#Rti-1>~V zf~!%_`A@05L-6av{{RrQcCyzri#E!}70R((l$e)mY$XfttIiYOzB;z~^pjiZMzTQnBkvNmOx^Zl80= zJR$HtXf9IYQG-m=?cyNCV`FI^)dSqG9Xk#y)-~I8e+}v}#JFECfIgJNtUx7-+)5<5 znBgJ^lj?qzr8T=xq}>oW*hNZ;cS}+#PF&G)R@EOI_z%N&^Z55skfzIzH_Y=u=Z-&^ z2EC_N@P@IdY2H5r{)pDu&1C8Pz6Na03XwR-P}d||UpK4Szp>N=Y84K6m;yhAMFJ?PKD^fcy_q`6L* z!9t9kL}vcc{vVH1_)m8%fkH&-CgMKtJev78!g}NoT}7f@Pa0U=8+(g+3U%2aI6i~| z!#={k$o-`C7&K3Un(InN-ziZ+{w6E{74QkswGBHhQVCjcfC@Col$(%34FO5|syGE%4vU}TR`Tb$)V8I6tz$5D=HS8(16lvCUewJWJs z2caX1Y|g}hIrgLnZ{XN~@OOz65CMq%z<<*-Tr#*;3^BDv6;Buy+;}kyct6C-#FAqm zOT|z0Bc-sL91ap69SX{*oz=vUA(?;8|&ts0f z^IP8(uH#P)UHO`6)v%l6wJJ)xfxtNawdF=lLi62dd)Sod{0-sx zC5Aa9yD{+378@A#1CdvJA^Sjh8^}qBsHa9sDlMO`UMaq|xoH|AtfQRQkNAokd8T(ETe!!6YWc_Dzs4^XXEEI#@yywQh7jEoD#L>n}A=)>LE`GJ->+wHd@m{XBKiXn5 zCQp?FZsZJP@Su~$dN_Q#t!TNe5&_cW2%|1+G%&@o-W^UOMLnyyN!#)_2-? zKTT7R)7(hFcPgqsOxFqUGf&rMyca$n@fD54>OpIA?;F2da7TWaHS3-*@I-$S{y6+C z()D{smfl$BYnxa8001w$>5t`CO)3=`~y0j|O}O(i-|XBDvJ3 zmrz*d7%`(^WBk=abN%Y}>w~eGi5m|i0$`v>F!Ngw}oBRor9u)$0xUA`JR<=L^ld!aldk9 z$mbyY(^}dKOLex13c|SBGtNCI=I9nF&kx9isyGJ+A1{6>Ak$Y-)KbnU-dUs|A21E0 z)9QJx2_sdukUVa?Unmbuae_ZO*YH)TYuRp|Be}nK9D{-~31=R-3Pp0)smV>q)|%#; zN7laqyfDpYYNx}W+BzNP0yBjBHhU$dr};tfXr)(;6yVQYUoTwPwlXDynSAcDoDW9o3K zILW{nueAOj_zK6s9uxa40iG*seTwq7U9d5hZs*k1sC+?YZf)a|;XK)&Vnz;0KGm(` zo7K}iD|S?DCNc-*Ny*i`=PTIhsd&mXp&nji^6%p3f-Ssp@nct2FNq~12kX>+71De+ z_-CQ`CgJY2DPX&@MIkh6=nQtVI6Y=?Pnvu4$4)U>o+9y0r-%GysLgvISCUo$vBB%w zz30HN>7FU@^lNt%H!(Vb1cNyqzgqPDy;?M2zRi)>EHo<4Z>jL##*c=V7oIJ@)z`_j z62_@-Z=+dT+QSh97Gh#yyq<9vr0j2@p_`!n`@(=^5K290`brfj~kr2oNkQiX~u6uz-+#_8y zL0UHeZsQ|0CzkCm%0OSQQ|L#%Bp@}x4(9+I9OELHXs_nEKXJHRnxPI`bG1XJH}xGx zd)Mes?2{OW;6I1Z3yjR~pvT@JAuMeD)m$^AV_1)?l zx*~fXzeN;OnFV8bzy3fM80(e)0MLbO);Ej4<`>33$~06d+Nt79Jj0OQiXQLL`4JX5A=dexTMtgr3kyM|7nqo`r}99QNi#|=I? zF6`up67svAM`A$)AIJ2stbgF2pB5wWx52Bg3*B6Knzw~6THQmp%+``IcvyQW-k*T3 zXfJ6&OR?QnUdp?VbJaX);20!lYh_Vz`I0uqcDNY^z8|yrZR0vYaR(NDK#VYxJ7V1-`tA-=utUD+}Vc!ha2XSkfWW{6k{% z`2@YS%n}&pw{KK&)3!%XYTF3?l$%{n+BK*-dpufh4|blb&2;>!=e z$_O0epy~CkKNkMYI^xA`V`t-?Y-zTNL=as_9Ii36WGK!t-n_|wVPmS^M<%VQUS8z# zo3cr8}81kR5EHxQkOKhveWTx9~XH40LDH(_}i`N(CWH{uA?oaPYfc`+$mL& z%dj90a83a|g?(}R4*t)}q4=sRy-Ig!rHsbV_BkNr`{ZDLHR>8a?7^XUB|=$P#(a5r;yL5&qOB9lwJ14GoOOL$yZLlqaR==t_K*t; zKm!PHu|z+;j=zAfnSL)^f5JcD!2&s3tB;+=d!PQbcHbF3G1>T^;vBZNvI!%yC0+jj zgfQ$Y=dX*tFnhZ>@9y6z7(QBOuc!2{9YxBaq#q?MPnkX=-J88}E!2V``AJ$<9S zyt|$Zi#TnBcEpa5r~xzXR0H*D`UzSpFg{*4oaIxw#%Wgn0BgIIN6Hz=-Pi!Un)(;^ zBk}q0pX~{vz6#r4KiNp_w4)3k!2W`~9>G4vrCdyZ)<_5#?57$2gY&H)0_qo9X1#BB zWEt=6WsZAwQgY6XoueMTD`f9;nX4-wy7MwLO3Hn>9qTf7F6t0&PhU#J_*>%0d~@*M z!F73RFRkfa5{0$YoTh6C!;A`Kn#N&I45c5wLB)fJWr(t z0FSgU;Z-Cn3aXIY@Cg-n!esvd!cV4dpkD>3H`6J_}?IEuCn&9|< zO=+I$X$k~Gp1gM83i?;}iPHy%yl(f#A2!-zC3PP+3=SI^9X7uM(!M*_JQJ?ypAzAV zLASM6Ys~pd4Iwm+ACD>r^Nj; z;n#?KH4cZZ+)d=9x~`$*TY1cI2w;ah#xawIJjU$PxKcJ02@o@;xKD&sJ5IvU(pw_$%X8(rGj4Q!_M?Moqku z9F|W{d{>tEk64pf)#ROy_bf;s(xmV{lP{MxwRnO%D@%DeKg8@ds*le#)PBw%59Ii_ z@z=t-0-<|3Z&u>$oZ)TbJLM<-0=W8-L}3*tV5wSirj(ib&G1*?&xJl5cwfW!RvsAA zY&=Lbn`kdJOM4_snOn+T`=kRoB%GY{-!QPNQPAP zJ=Aulpad{10mmO&m@#jZ1|W>?>?#H-Mn^fudIQ>}SYx@pD#LPtu;Z$)e7!sC9#9e3~2bK-rD0v@YG2Xkqx!Wa;=;d`LIW(VmbO()4n3o2AQc@-^V8S z<&h=~r-J++<<5S!wi4e8~dkP#(3^YMN#mPzfbY#vZ#6vM|lJ&p8k+Iep}PysuYNaOQArF`GL z8FC+ePH?FOJ9ItY;BK9&>$+q3t5tVxTK6vw{#FS80EIyQe_Df9_>toe4@auOtHo<+ z`@(J7-d1&F{{U-n7(MGR;h*h6;olK!Bf_2z(zP!U>ejIXEH-d#iX{Xu%@~+=y?%Fytkxou+$uFB)A2#^A<30Qrtrnkk zXL98WOs@%(&5)is$QWP8HNf~5$5haOzGs)sX&PZL;Fc|x$oJ1m^j{iyd&EarR)^uE z*#6|)s%;89v5r`i*PfWJ1LG&gTmJxq_m;XgvEgW$r9^Ks-sFZt${T0|VDQ3}Vb5xD zT7_9EPufaI_95c$_((K_lt_Hk`CSiHHQW3;wT&%4)113@HQ}EIW4-Z&lHSQ}ExnZR z86)!s81PR|Y<2gqbnp~S1*|Z)KQ>1`^@TObRm9U1RnCe$$M(&8o4*F=dR4L+8t(0+ zk}xy5QF1u?u&Y9JvqqmP_Klw@h{WAGDn6|G z`}R1wTQ3J_b8b;QSCZSw9^QPZFvImZ{449i#N>=^J?r4#gjV|2nQu0!p}dn#YcH7k za`EyaoUc{EGV}DJ%`$Sx+OJ{#EGGmCpjSY|f@t z^5Z*++mFJjy6z#t`A<<+uH1;RoM3VZszPJs=kUi~D|479af7?3sO&1VvJoIBAfH}p z%P^4{dSrFwa?6dmDt8_^JPPW(AUv-H_?5uV z?uq06xtilGE_b?yTmlCNwOiQ&>N;Ja%9R{&O4RYhqdNnA)AXv0Nn$|bwtZ^Eav0GS zu&g;?eSgj=6hpL<#g71R4|-CHFhb!*1_uQGbema=6*&~~``yDEh&=mHA%Xm(>7La! zh40ud;J8E~;c(-gqqwI_Xv#9ma1Tt>=>oq#SYeJk(t3?MJCa>%`gPxq^fb1bN0?gN zqsHKXqvUT-QC$|lr6#Lxu>h+izbHRBZ^=rJ%;LQFU(`Rcd|BZ*yuiO``)aD=s|b*f z>t2tiYcNA>vPmHGO7oM_yo!)fpCdkwl}S{DYDH?aJZs`FfOQQENtkK($QimMgN4sr z6#$Rd@voA+Vf#1u&&N0IGRbA-$lrf(-H(0+eVOC!eRWIUC(Ho>>P>lfj6N>t-V`wD zHgk)OQsIJafp@<>fF0|RzE<3JKB9~zD5WKNGM~U-+0G9D!wX!jcNYzq-avo`9dY;{ z=T<&6cxuZ<@%@~p6%avfB&?uteqMxE(EbdCTSBr1*{zr=mW}@KJ#c;N=g*J&ki7Aw z+-ksx;MvEy>H1YT>CAF-bIwrNBz|gqQHNI4yl-=Ht6xbd^NYnA{INuY+UKd?AShiLXnCC$3p!~z0GhDuf z;mcUn08x^7VP5OTN#WFD?WMFlm4r^K=1KaV&EUTQ=ne64FMK_HaxHC`dD25DWu3<@ z$R}|ua!BBN^{=+R7f1mI((W z^w0Pj`*Y#WoNfFq4p%E7d3Sf@_56i!(Y;EX(&%B1m$9bd9=aP60E@LxdaTOQzT$E~ zJxy7fF_vB2XFODJg^k=1*1aR<#D*|(+lRGUNJFq=k~{lUP?SlCJadeixClt)C_@rH z@SqA8Aq>Rx?~07b*vLD5s#jhz!zUdxibhb<1GE9g3GMGd8y*p0+VzRta#-U(?wa`j z0ORaFcgEisg(?_dAtOD1bd~lOhDZEVwm|X&9D97GzD)S{WT)dtislC_Ztw<2C(2IM zq+O8WuOrT_A>Qv3C6`P8=7e`O6Mh@0I(W1d0o zG3!e%qGO%~W0Y;dN~t;e(rvwsOyg>h-m@%?7s-JR0A9UKRi55Pof%bGS+<{1?^=Mp z%xol0%&bEO9HvKvcSP`js2RXg#!-mLt5{jF?mJSS^$ZUo77 zYO}_voRwk5K>&l;f-(po*LU!tJSCubCfK&IVdNx08D8N4>GiJ!`2PU#ZqLW}GtJ@s zR?_0wZr&i8HwsTU>&G>{1qswqo3w6eHP0tkmsPX2hsOH1#5*4rYubhOrR7VMVyKdW z$WMG`z3=vG@$JacZDO8M)~ra4+nxtX`LD&_1?JJU>1`yvwYgx}A{i8)!~AR#7@T7ET(IhS_P2I# zZ=KlZp0%BDhEJ7Kb3e#4(0ZEC`#+m=x3TVPPe#(C)^6j12Fr~!`CCH<6l*6 zG(H*HQ+H=+`#X3E{8i%nQn9pF8fp7w#mB3Rh?Hmju7BVrzQUDGnQt4(CO3dSZ{jD` zxNn3$4v)d!9l5iL4YN#R%!KaqBp{MbJMk{z;0P8(M1#(g=6@%XF<3g>;C|u3fQcF7My4|9OIS$ z0MLad2L~KsN6d4aV>G}C``zH|#C>_&};tFto&!r~qs4ZFZ2kkF4$BgcEE0je#c8;rU6oBJ9 zq{OZC`AE;UE90F?W_?FYPcaKjWVygU-eb2T>5tOB)%f+J!C~;nRKY zhmp@7@6Xo0Dbww~-Qu}2xsJvN;~S20NgRD~UoDG|zU0re%dPC}yPDq?Etc0ru)m%? zh8rT~{ZE!Z&*NSp`#$_^zW5LELr?J~xRQN6^J}Tuq5lAni)SNnAMGi_FS`5Jwtmu6 zNIVCmN5YGya(FqwC^7WLYvlWjQiTB=lgH;<<&aXK`MT(G=F@7r<>-Fo_y@+?KZ>-A z9cxIuk5bZgIE2>sF`gYr{Rlh|c?1w^vII(s>Nyz%SLMg-ui}3nd==58zrD1%x$s@& z+nY<1{bX)V4DkN|bo9#fZ)44Vg7|adBzIapt@0B+t=vg8F3Y#fMi~d#)jDdNxo>nR zRQ8EUt259g*x{MTY#uT?cC1Za@))9Gg?z$JSbJ9q;-8Eb*3zUf5+uPsTXn8qSNMh@ ziEb|?7S{2oZJ>r`C-^`e`&ILHI%7$#S-axD5^35Ui{I)Kh*btbWAigt%s&)=X>099 zSFz9u48Vgbo)C2WO=EmX)-^90>k?e*R}xt1tmnwJR?MzDaodXIS4XyqfQk_mN;~tP zuf0zqddRlj?Gq=$`h4*lo7<^dE=x19>z<~(r_7&HH$4v#us+_Y0in^`(?7WJ&25L&()l>A9GF3&ad^;{txPMDr%K0b^icA z_#dI>+N677SYrgQ3K!Ua_4%gglN~<(Dbe=4aw~=%h$A1ZE6y%VjmOLK{y4|=s&`i_ z433$@1CBnm=|Me@E~UOB^y~Hn_>~r~;Voyu*G{H=B7f~2J~A+V$vG{@s96gywS7{< z4$X!Do|*4olK%j*zr-7l1o-Dq@e~p}KAJq4<3pc5(c3acM{|so{{U%M*1uP+wM$)R zO@j8yb-A;-jb@H$h-GA9m0*1cBDzwxho3F(L#RloqXaW<8-YAkzX-|)igcyNCgfm_ zaal6SwZ3z~9ZhNYP!r;f7i*{=YF;taRV~Rq3&dmoCwCd?^5g#b6_X(i^5Y}0_pL7! z9P4*ECj)OE@DW*s10tv=uO_+(EJOff>xz&a{PV%|s>kF!9Mp@49Zp9%pa~grI^u{F zLK_T7C%b{f!^)#;#nHfMvCB)2ksjgKkybH{WD)MctZIud`YF=1XQ@QlqzGE+qVZjc|Cs$`;X&x zj@O(vCDqBe@a>E%ittT8;r^B3`>1TvLvg9xW=ZCpjH30y_chpfx8n}AtU>1L za72>^`6Grb0CU(A-ngACUrlML>vyp1T zk3msgBT7|Q0Mw}`Ac7C$N?0-K7qtLZiXSZ-aQvzi8@J$*>r=Bk4pbEf8K{6NNDMjP zW`H92rU3BIhq5>a^7$*xjJq+hOBLt|>t37jLo4BZ1Ri~V?~3z?wg7_}Y;~+9xvX{` zn~)a5wnjxu8!6!KQbtGzfN8GgG{{oTo-|)VYR&j5Ah$$xIY;9Uf)=_(=|4ae6}+J z%Z!#o!+wUnQufL#`#B)EP-9_(x397Kj@8D;=4m>ESzf4Me&gfil|4te?mJh{!{gU5#--O`4^jgR zbU#}4zxZ1B4We90ZDg8*GGl9%i!0bM1m}X;>C>f6Yy@`Eh54f+AdG3 zhAW?KD^Sy!?a3ZXjBZa(xb_v7v~hgLQ>TTe4q6oT?)CgX%*F6P8f4o0gb~AIZm}i@ z1>b>>qOa>){tcWo;OB_>Jl0&+Z);~dCRMH^^B51}AYfFw9qd+~Ak%b9cUHQRc$(q5 zgav^M^*u=R`qvaM?JwNMtkb6N(DI+#cf+6BJ`;~ox@K6RmIzS@>-){jKDjurpZ*x# zJQ}{76*oKMVsb$_-HttYudaV>jXd4_9(#}jCz~9>h~$$ZwtcccoqUVoTlDbN^`^2^ z$#12EnUlK_vm^1^N8)SgtfIM3i&ArLPpS2H!;46?PmJ20ihwP&(u=s1ouDJe9Q{Dv zSMslT)%+43SUf@D^h;e_pf?Hp7fN{`j+s8c*1mJ_a~)6OZl&TIClgv*#1=I}ym<N8U_+X=%q+(jAMd5vCU~p&gkZ?qfE}xwWQW<8JSucBKahV zk1E~4t2=^*VhG#EUbPmdrlQQZaFZ3`7-wDti|E6@vFa*B-7GttY$xvmYpYX;RB+pZ z6Ty4xy@tZ`W3inW!_N38u?_M%^*1Z zH!BL+_`&gy!*+W0ufuDbc{MFxTq$WHLx3$j)&W_MsNu2bE9L!4_fydPMR%m$61ts= z3oD4E8$+~gSsY`z1Ql<3;KkEvr_}bc`rhlebI<-M{?a<{iS>)C4Kiso`)Finq`GFo z$T&D2-nHnTvnHKq;ZGQ8{wCJ$4feq8E6jYx$zB`qBv;LTB=G&uiGD5ITIj{>Zs#v@ zimlQ?mLt=Xn)bhdV^sK!2DPJVI$0hh(WEabY3t?7J-aRzR$sbKPCi_AF(^V;&_x2N;XJ6!N+>}AH<$3e;xctx`x3_rhAR5 zJCMKUHQ_Q#<6nlJC~LhMWuDqWw&KqIQwqw5f*DWfLE!YN3F8kH$t<7Pb`a>dQ{+A0 z+SW-_9;%0cx%I(6N{30#+N&KApRrO-51IVVul9xbZ*^mFXQ;^-eL`6z+@Z2eLl``E z&qMXEGw^k{+jRkIhZ3t{qGR(ZtzQ!Og2TWz?QP#aV@EiM@C!P^{hh}3-sGHc`?*xJhf0OBW(HIEuz zMJm|5rdw#F`;c3%RtUiLKY0HDy2ie~xr~X65^_2ZTAC2$O|!+v)#s^V2|w3l4hMS9 zzH-Fm5~m>TI3OQNwIrK2cE_zXV-gQfO6ok)J6H@>kw)^otgDUkbtATY@rtn5TGoUOQpVYz_(>V3d`sxg5`MN+Z?GP&e+>?wSrlX1xG4@$Wchd>Ae)}x*?E);yc zP4Sn-XKwZvds{7l2bP2rRGx#6#BmZ%9oe_;W&;JiF;L!ahTaQ*Gm_)y3%fqp z_p4&cAgeau&m(Qz;~Py&aTvFXG+Y@saU%=^-+(G^YC`~$;qF;LK<5lkdds)5k{fyD zE@hC(yaqT5Jq8C#*&;}kNShBIIVT;t%~!UOq=C$igfaX3Ko}>EKf;9U1lD%3E~fzB9Fgu% zRnJg;$4|n(OE9N8byZmPKCdmruV(49(#$;y3IW;hVKr@Q;eMEiG>Dh?P9!B6%GAm^_j()Ss<;=f$lV zHJ=U307w?{Kbqc2;`1ZVb#?BhzBKXAj&p5A(5OFja(Jy{ zUcFhVLHpWu?0vQq46#(XsN#K#>lg69HQN1Gd-Sp3KNo*zTYrWU+{<_3>tif>huJ)` z;blNoSTl2;cXjEC@Y^``{{Rwd;=@C`y1FIGthpg}=kF4GW199~6nH-S#@hQ`4Ibj$ zxh7l9O69I5eD}%gU8jXS2%a8^V~XGA0B?WdYWpe`r3y>hJHP9(@|lhXFssVzbAN{a z0GqeqjX#7x2qDq@J3gnb-#zqy;_zLRH)@veO{i3^Dz!Eil-ih&x4;2 zCGq!*S^z(BZwpT;_8bBEpVGdZ@R!4DUk_Rs*4<;6@#ZWUR~@oJ>+EZn{funlk$ho# zgZCiAVy+h zXJrRJT=)DsQ*NxT5>{a3!zl9s#|k|?&T7+(xMiKAba>C*h~#4@oS&y`b*q+lf-=3-tHu1$*Zz@*u8PAx!2iu&FTC$d= z5tQaaFiv_@R?m{RwoDOdQ$m{qaa}8wMD;gC5Xu9nzN;87dqw3 z#S0{Hp!wx~$F>KpW?2edrqINNOyHdR;-~Xr+S{0H$3B%i{3^J)c^X}0z+7Ohyd;D5 z1mdx7{sdh?BR-kp%ezdS{zb$KBqZaU41&4q!K|d_wvEjqp!b!J5%~S7#c!fY%Bi~c zc`e~V)sM=#1JEiHUl?inUz4ayDO2W8aS#BWI0TSCO8YzF2kfWg?P}sH**rz2>Mds> zk{e)>Mo8=j7#tJVIVYO=1Zg_T z&=s0x8F@%Ommx>KPip#?{uthG6k2F6;+NCyba!7pmchLFmB|EdVeiOLfXJch-Z`AIX=Igbm8c_RK1?Z4l2BA)%J+;j~n<0OSkYg zspi8R7Vuff`~L5jv3F#CLa6*Kv^t-_{{RO~GJ!mrY*G?CZX2=rFt1Mip!7z!_!r}N zf|qB}?p8mSa}36K_pV#v;zcKbbU5vR`!KSD%U;1ewcGk)xv@*x$weJFSM4C=`<_GN zTUhLF3Au%c2P-NJmHax_2YUd&C+ymkD98A=VaNUT(!KM?z8hQ1eC-4S&3Qe?g;qI< z01v{rJ*1K9#@0AP;3a|0)bg37JnwUoYmf1R$ERAzkb*PR*SlM3OFU9rFa&|}`qz$p zPthc^5~z&#&$Vk#tCX!G`4z5@nLJ4>t#d4gAd|&o=ytDntHPmLMkMV6lblz3W#Fw( z#~v=Q&@|{om-qJz1VPT#412Ncpk$NS177K-d?)bd!mkeMpV@b-;-3)7ZVk??VQ8%_ z0ANZ$tT#U(WzGQ@`d6(ve(l)u=9FfWJQBxA)jTb6ajxA&ZEoHMk55J;a&Gx|W3g5K zb;Nj%&}sTymeELAiS9+l^suAXnL zK!|U7G1JpE$4UFwf7OLs;j;d&dCj}J$0L!!agaYB@Tyw8tYAyR$-hiFR^Wr$y?Sj)-0>$Cm5ZOVpN%cNJ>y&0@8>q~U1_&5 z#UL3eaH+oE1G)2620Qex)h~eBwxB#Wd8KMrtEQWI1hLoxKhZqFx=VZx$uF1}{gzt% zzW8hKcTtO8wbY<#zTaso&W1b#8!5;j5zivOLB1G#L%Ew-xYm3}6p5%^M7Hx?Tf#O> z6B`VwI!M1a%mBzEBZ}#$<9o#9SGK3U-8!*o_XK9aAdYtT6|La;19-PdAbW z$J_Xh%K8EPM)<0N3M971FhY11~#1k0Ki3Npa6QG zTDjttEw5c|Cm$w%?~znvBu9jvuv; z!;gT1OKpEx`)0Zmdgyv!6Wx$TS9r)+f%S4dfviv1hxV?#{ieK0@d>VU+g%FJOItIh z>Cv~DHqh(SXIKf`M0KxCpxqldZZ;M=6zR@k!%dy|P zf6N%?I5@)g>C+e-SCjaM#kYPS@{&-n+d=?HP@D`50)0+DD%uqJUD?lD5$!ZZc;C#M zabi>+_4NPgS7d|Tm9_$m*E zbblCXUKIGBp3tZt>R`>0elUKlrWSzl!>Jz3_L6 zG_Mj{k&-m~m3b5W==gO%?fm?0C&m2em?7T-oCt#e{}JD*4nRvn&Q$}?k(goO&rlS z~sy-9`(lfhr?QgA)~aqDyO1J$j7C8jByfzvq#@5aFe;~_x>o- z=7vWTDF9`MTvwmn__EIOX(5LuHOol&zys@EC$Halqe^y;Hnde89inzWmh4w2eR-|w zP&8N9@;qI9n81!d`{Z@}b6WdpPS!MVidH=r$6pvMY^0JMHJ0Y>SIa`2q+a>{CjBZe zfs)I6<82yg+`QA@D>JdlJQg`Wg?Q^};v0{ZOB2U6>t75nV|{k3kUx$te4kdkbPZezNfsm}K-L}~c#k-y*r*1V%b@XfBX zulNVT%@{_DPm<>A=IFq?DC5^|e-U3nRqJGYr4?x1osaBisHU59ec=6VS`Bp}OU*7x zMg`S@82 z=3Dr;!!x!1o?qt&v+P^UOJ!$C~O`%ie?~}%81FrD62g05pBfMv) z`-Zr^i8kSrfH*koU7v*lp9*+|RBby5Aoe>AaO)J2p~>WS2C3|UZpi=<$$&ULy4Cn$ z1`tWW2RQFk5@*&y?Td3A77QyaCA(lx)jo^&;r#nX(LI%~(%zXt>YqIh5`HAmR z86M$wC@xPJQJm9Bu@cLD6iiY(a{P=F(DPe98PR^%BV0-klB(WXk;6By(0@9~veIUj zLT6=#Q=NzJoMSw8`@^rTcTmY3b}+0=9b@?ruN(ngwD9uyq>eh(;**S7@b8E|80vbj z{1gi6{M)zoJ%xlC{PVVU?r6+0r@1nrz&m7`c`#?nyl{(>=XwiOS7iRb%NelZsM>MRfN@pO3tG;lC01V&YwA zN41{$BU=QQWv$F&1gEGRFCkhKTp&8M?3Lr;l1sbgmvGEJ}-nt;;#{0sk76UrIZ-?6#J?L z0DTGM*D>(h!*OVy6So?K(bz?-FplQta#SP*#z7zx^AXRmHR=BV7yMd&FkRWqBA5Fj z+3*2Vml?p@?#J`ux&Hv#kHgY@JNQlDi0)HnudClnb#e#%v5qK}Vu*I*%*pq!R+OcP zaiQJ*3248sBj)i9Lz<*k%kw`_{tkEpL-=pt4LeBi{L6V_P)=`AgA1l$KX?e^X&Aul z0Iln$JDBbn&UTSsC4Rvl7iPQgExv)OUKy<;h)Dx6C+z&-sVAW5aoex0eQ$8NnS%Of z+NxBXA1UA}oZ7w2z;iKhgpxMo^!%!EyKl+>z{#mn+j04`>PM|ekpPTFM?I@8i@5|S z-ghM642rI|_V;&E!xVv}L6d`=RMR|xW!g`eN6W`r&d_v0VLYdAmhuvDoP(aE`_cna z7-TF7&Iqe456S__>za`Pbzb=I>rq@WjAsXo@F)?d;i+8shRIJ&$3OSUua^Eh*tCBZ zd{cBE=6kMHPhlDX`q$LH7h?L|i6afT%zGk`jsp5##v|wD0nEAd$ zKbLB4=v00qfwNPx<8rjCy>Xrk9Cprmrrk+(ZyropQisbKzq}{qGWHFf(~CC9^F6s)aypwZ{`x@pYVR>;s?|%fZYr+Ez>VjGQn7n(EbLv3k36^-zx1qu^AZ{JdD?+d<%Tj+~np?2k2|h#YIYtlRB{Saj2R*y;?h4_;Pl*1CVRNz9jfE&i+EeHD(_$ zAPVfhChFJz5_vAIVw!7FlF`JuW%c8@{#D^RhsSGT=g&J%c|+7!gF!jF#QSO-(T&q7 z-}pAd)kKmYF2@+pBj4#>P4QdBRz4Gjp^4Po5tFp@TD~p#%WplzlG@nGs9g;CYsigH zsr9c4*X^5Ey`NClucI?NZt_us753u3j}1=EN~1aPGLu$`$?AH=--xw2F61P;e5gAr zio(}*Az^OT@U~}hhH?Bp!nQS?YTnu=hRp}RKoKZ7&eA_G07~#uc@6LZ(Nbh&F zoA5$|)O8T|ThK(cvFfa}?pZ@?=RrLat_K?Vo zfE?iT;DBrH@7ZBOd=K#YsVt$c0A@KS_wUVoCp>dJ4(dQ<@6`P|*WF*TqO$xA@c#A= z+wM+4{{W`%R}(6m9=SynRTu?gc+Bna^~vX|bpHT&R^4ED;T}&7+(#JQBfMy!cO}3S zm>edTqh9Opi*yMJoIKC>LG<@N!o3Sa(&5mo7T!Fu>h4F(=hW1e7Hg(yu-ilelt7~c zJoi6|szIeU>u%SLD>2;B!~z8!@<%m06}hb>%t6AxwnbF4y8A`cirC#Bwg|3T<6ntY@`Zt}h{2B{)TmWiNr$^Yt{Zc2_Nyrk%oW z+)o+nn&3Qb@V`g#Sz~u$4aAZRGr9s#*1ZUR@ryq|coiIq3uN`BD5-8Z$;V^Pbt_#* zL-2LQznZf(v_UP&j|`E4fVff4K3sZI_!~>P6C>Xf=CbZ61wIwEv1SnGLxLMXM?-co}|`Xn%vi)OBlZpw8*vX3SA|a%!c53ETi~? z3=!?YKmNQ|ihL%s{>jj1@bj^2pAOFYRE3W$iT`IQ-0RzxT~~c*rRwHPH2NQfl=3 zm%Kx2B!q@s{cFuN9X=$uW&kT5idQ+WU)C*Ifdq6NtIoCEJjXCOBc9w>lGT~)r*v}q zMv7blpHKtoZp# zCQ=2997SUehrp8xZZfr%OF-#IABi|rQ!RFLT$ve zppR&8G@Pj&vx@EfDXT%R_=+t*O2q37!+pe9+RcxZRQimPPj9VipDMC2Y02H5%i;e3 zhk9)B+uYm665#+L&|rhyA6oPa4HhI+-x`U40I(P&*0+ZIGZu}c!5+}AMmlGoTHmqJ zJmzO3YK~8^tx?AG$xX%4-ig|W7D5=MN*E4nrVs2R`m ztRD;5t<ZHagT_>UjdtE1(-Zr5PHF6-Eez}Bx)9qj@4*$SGHBcJMozbM7lJnb z0O%sK;f%;ZW7Dv$4-?6=UAh?l=>Gu6MOM>oE-xek2wF^>7VJM7=`kitb=n9VcdRcS zd`R%8!u==vN5y*ehJk5}sl1dc$?S+S&VStoz5w{k{{RIG_>nHNtoV1s+AWuYTF&Zg zDJPTtF8LZaDBm*y8XT$UryjNPuCb`=J~7p%)pfl>^HHJA6apt>L4HaWiu#AKj0DsZ>H+;n~f*z_cG)H zOP(>$uS(I;Eoakj?Jwd|uW3AYEA>YY{V7`GS|3Y)!CC$%UHFIN=AYpNnEwD~_;XB+ zyrnr`v|N7i*!%1e52x0?FYw=r^)CzR(CRu?sduC5FtBK^EarG+L+t87ADw*%`)=yY zzqId--u}`@GF?S9GXa%&9tfH&dju*!3h_U-czaMywzfmX*DS={?I2|8Rsn! zVV|36IL|?xXNt_a)h@2&+Z~Z!cxQ2e`BthnMiQ4Z(CsWdX(p1JptH4%Ao*56Tz**s zzK8e);^_V$_)oi|a5!$WsxD@811cUMvfs`BodMv_Knk;!IuIV?%ZB=;oqQ(9V= zk%=8R{Az@KvGAMz3Xky@!IqI&c&kU#{A*;KdGgBEw`#ZmC~z1MF`t=9IqP3$d=~w` zJ`;Rnk{b!NDLfgj$abxVh*=^@52SYh`EB%Kr`o?6*4fnbHDWmPkicN|%>aKxaz^Zm z$m_L$WMRs(`h(ni(=K7$gO9@%_>b_1_NDlr@J4H7@Yjkij+YZ;=-PuDn-?9&l*i@z zp;9aKYxX|nMlve-;7ns2w(ssjxkm9v4}r(^q>s?0E+Lk!#V*V^*uk_uQr62+EnLg@7ld9 z;?jfRtqAdu#~J?sa=hXKh=3}F>EEZlVJ*#Lu;mPqvBu-c#%g3>7w?`9Pkfq+W?5K- zBoD1mX^;Y-DxzyfCna=32d$~0nXYiGA%;F*H*P_Tia-^U?&X}(T7$aL&b4g zm&3as3iy8i0R9o_?sSMgR{qXO+3d;Q4n$3mhyC0SYV-w-jG4#^qnuVJi=|Pg3uVA* zWLyvSLCHVLxbZG3l$-2!VN|7BDR)OTqO-ap$hecC!tqjT_6sLFihwxxs~U7-DR%cA zD%PmvCU6*IkZa-^KK2sS@-GtU3vyqvC(^h}{{RhTh#+M8cCTU8;QjYNLF%X0xqU{^ z0?e`S4tc1HtB5D_s0ngG|#dn4M2fLH32}CK1FVNk87fem!z~*Qe-qP-uS} ztvvT%FHqC1($&sEWjRxW-~RxvE9H40lTFp;xK?QHB?0oB5DS0$>(MnIi29zhqUl!J z#7TaZ4jK!nkCAl=0D-nu^d~rALBmNWy7>;?W`fjJD>PkMxdv9_vk>pCUWP0EeR-`{MZKo^hF~xPK zbBfj_i2>iZU}HS@sHTvt!){JFAbL~MMqmH{0DB68W+a7-^PC!lknL_B-Czl80W~g z85#coc>e%O(M8EC6U?Kz$wJb$)W?{|vW$~kdUu31JDsJY7Lgu?;O#&6&sy%|v9ZwL zf3u`^=mrZY%QxbAqQH$s49q0QRZ!U6eNF{+Lk`;Jk>&EQ#`U>F~p#byIMaLsrmelaDEg(-h;1w_!1E`N@T1omBPONzr|}0(_)+1BbsL3GwJ_Tf zXDsdb_OB`UE23WOcNgChJWkBlFSuAmFGxY^;2wvtucE=_@pPUps`nO&e>3d7yR*i` z<0b7D9-H@`{!7349*?C%Ev>}y-AZSgDB(+)-JQ4GGZ&B`&H|_aW8b;0x4SXJ8BD)C z05SSjPlokh?F}u+0V8X|LlrH!?8#y>2U0rLqv2Gx?ecWpj=w?Lw5c0OsUs-6#WZ^dQHZo@DEee zt+LmiAG@~JB4N}RWma$ebhT=DW5&^VufiH`uWaF>xq)On^f>0eGdQEmIMiK#L+$b^ zywu%3%=7;Mik=2f6GWogf3xZ~@{5Z(i6A6{JREga91;E%;t8IAC)OGqC*UmE_ZB>9g1=X@gLTz!F6?bs*8xB0I$fQcMpH_-n}^D9Ac7|hYYB>N!}{w zfAF8ec9&Z1z4D>{&9>Sgg_rNhGB@<-JA3n9eg6Oj1lORv)Vw33AqGo3S*MYD?eiHx z{SeorcxT2o9u(7_>h5rYG|xSHbQSU6#_t+jc<;vAhOcr-^G?{*oa{lukIK5T$V#>; zPog>ToU~~2t=aWw>@TUro&nTTVwuDFUSa+f+l+pd_IHH7GH5z>n{B3elUKH}zJ)gZ zqITO8C?EpO(RzWC#eQV|$(|;@()Ejb6uD@0`{}%?ld7|Gu%AwN{A=lN7|8|XQnYBy z<~A>GS8$U9l`HNEQ;x>JQo`iR8yh~S<=DJ?!qt_JyzL$d#M&!>yE!=i9oF8AC+bUP1o=>(|$R2EX8- z8YhZmx6}M{r>=p1$8YwPmR`}0IWC7UAJlFiO8M;9A;e%GGWVi-m>kNMC0Xdts-?8a zR>3&zDGW**f$#LGEHzs_XHSazPr8Qw#$?|W&9s6@NWeqW6@6rB8d%lL?6L$n z;B*Hb{{UZlz}U!BbZ!}11#3AJpD+>#Z1cxlVyr`8BDz?jQZ2R|Y&i?+D^?p(88Wjg zZrl#@&;I~gsN6HH_z)oE?vgJ34^Gud++%I+#1Y6BV@A>emIpWk`PPh95n4b3ZpyCZ zRc?7FkJge@Y2m>NfQ%k_>HO-(ooy7Wz0r;iFmf};ztW+A?Iz&KWG)WnNffu2ASyHUr#uzU zKN_{VJpS@`B#h>$yYc92PX5W`bCK4wE+HbmiYLoe-1_tO8rNafyfxx)4NMWPEbimf zVMgTnZlPG?+2ddP=vUJhR-!4EMPyQ^J;qLQKD<}vx56KYxBmbMe0isMlFmQ0BqYUk zYn%&+8;3*hj1YSeEA&spzA)1KeW2UxnhoM#Y4eQkQ?=r3a;&{W1Hm86SD%Td)VaDd znKFln^r>}wS>jpEq|U*_iO9}-k3&{%bmJYYcF!W+nBrA^+?FG~PkPVhsv;1}$vGr7 z7Ix@H@JE@{fx#m^jdNYtWN=-?UUPRc4WLPL$Njf@_(s^ho5&f7Sr;4*2ep0O`!RpX7ts07&vDcKyS+H>XH#R<^{s5W92>n09wKLm3q@hW2T`$zHnQf z)suZqqOW96;b1&9;IBT&D#>vnWqI;^#wV8`a@joweL7cRZxh>DMv^}HddS;C<-71J z9xFuqO_VI4TItY!9BBGt7fys8yC!RB2fRAe)_|42u zWC>XpAd-K&dk^RIuXZZO&9-^J#~%fzvG7yHHWtxuo_lZ=7~nf^UAfOram{{rXg&kE zUmD!_XIZyMFX1a2+asjO8DJY31cAZi1IK#(8}YurnoflVoVO6&BeR)qt}ZbINTlJU zBepr}I#JKwc>y}hh++^+s@?S=+=6IMKl^_kft zQlZX1f|n>c$?0;2m1g?Zr6h=?TShi7zB-@Iw>5~8%E>Jg3ew~|`**Fltl;qenfx)T zE=m5iI(ZyRYuXGq`8{qk;GudlR|o-XFP1ri?;BffS;gWFLC% z^hg>ldd!3w^FS`A1dnmjxJ!HcJvUpo(=CWtZT3c6uIDHJ0Igg0TJ6aAfu-31Bes#! zM34`@cM!?=4X5#|L^OJh$A|2v)MdN4Lp+a+BOjG;0O|fUd3MDZNYqB7pizJ+CXg(I z8eo(f=sAzZuiKx&>){XDr^e|LY=cpj9acU%`SB|`{{X*&O7e{|F(M8D9-_Xl{{Vuc zXlZHj$HN+us8OhB3XDMN(9aT()+G`LTh{G5VAERjIrZ*7okqpaP^|*H__L z<4a3{D=AR<2+lw}e{>E_WO$dwjWpk8wOoL3NF6DG)PC7MA89oI0EJ%=RxdKo#NHRS zwz!b;1>K@7Pm}6XXZ`SN=9JZ4$c`8zXKsN|6Zi`KV*QgmE8%~Qzq0p-G>;c()|&iU zCZlwa$9S8(mk!%qeGb`3{A=5M3-BMnKMivyhde2z>DL6E*FxD|X6HP+0@(J=W;61y z;AiZGDm^7Y??j% zm$G29t>)ELW7G_E9lsBH`$tW()b2I=%ggfswh@S}E#l|P8Tpu#-MIPy1!(Gt3R*Om z1c+n#m}eC(Dd@uXKRvu}{{RH*lf_;Qk54+BHhQco(pyjDf|0rY5>y5%cn7bj_x$hp zsqml0e+GP0aiDmT#(gsWBa}P0#WHqy-=nGZABYEv{qK`hwVL9_DC1K#)yk}DK_|-x z<|jVD)*r?11NaNadKROnc;iB|)->B#MBYrc=1B%Y$CtO}R^tP12{l$$u#dnvZuJi< zYTU3v?Ns7PCz?iPG9H;Gzf62t{{RH5vGGmR*Zvgo8~92KkKRS2>QOb|whi}C$_Qe8 zdf@O0#!tb%EAR;L7mM}34}G>BP4uhjteW-(D;&)mlx9$Q0F^k+D*?twrkZxysyn^V=2$|(<16}(`u9^2+`%i6y) zWr!ik>0h+Ju#bh)!hf=FfT7w1x7IRhlAl(dN0a{mK`K8A0QQTBk%=!DZhDTjO6J8_ z?}r)w;r^AOB%sEpjzA`|ZmtYLh&&JHngGW5y&E45=t`gh8MtrvE6Zbf5JVX|aDOhf z>faS)^L#y^x8B}K>DS~H=FrL{Or{7tbn9I5+}1k`fdhqaxr(!bvakb;a&zrXgC!M@ z1K4}iw(-evE2L4G0po$6&ZM$sF3}E0BO@IJGTB^iFY__=JXVFiiFC1`aFGGqIXJ6v zczs4$rGLOwIV4hqpF=ZoRvct?0-ZC*78*tf8>hWD#<#=5)|Pg**5cby<_dpn!=bqKKcVZgdg8*OC1`ZNW*df5$pjEYV|(WzGgWn#xhKIu%6E5uZyM)~0qLn+Nzu6`$fy4oIWQ zSn=w-i5da)labmkIT}qJV)S& z^<@%UtHE@qB~*Vre=%AruGVDoqs(+43q=%y&f*~PADTHp=%>_woL8=VHuyVls%w_g zGdz}YpEg)N@-Q6%9Wk7Bu0{%iUr2l?vu!8CfJgwk zxNOV^-i)4$jP@VSx@ddz+~%&W4Yet1e-AWkTai7bj8?ZGfRAi~Hpg?70=f$;i|Ydz zx4Du?fCCe;f97*nkPFR0(LZ>BMGx||Yoc73*K(-hxj%yv6QS!t$=b3n1n@pe>e@9$P;rMR1XsI- zYH>{PF)6}sCTy|EbnUqB1oR_{*MLQ&Y0o{wEO5Y^nU4SfDo-U;?!XK^>*s&lC*uL| zcY@;Z_Mb5tj;g^9!}AF9gZZ96I{Hk%2Uj-5Q^C<+6Z@A}@<)e?uM7Z{m&+gOlesm>e$Jj4 zkKwm~rPnW1d9lJ~c0b1}as^)aF{90_c)L>ZE~LBe?wGQd{skwu>0f=1R25k&f5F46 zMR%8f)t@JZbzB!e@hZEw*>?R8Yw-S-nl_21*vBJA>g43MNo}W`bU#z;R%VIgn6CZg zk&;Jz({9>1R@6Iytugs>*v8(tAI_wC7BX0`V0P!64oiIpa%f0!jUe;p?3sDe^34k`{w@^KQy;Kt0!? z^<3cbhC6>8e{TLDwuzLSoAX7Tf^79UDF@& zTU%{BmQqzZ^WMB0R`E;f7YMH5qbD1)gN*mDt-dS#9<%ZGiY|10L|9xn`FzCR8yw(< zQOM*GmF_<2>t8otd?3}lF?Oq~X>&^)XK&gq$DIR={{VSkZ&%d?^iwX6HSZ5QM7Rag>o^{y_>?i3&UbwAke_8&~?ct z13s1G-x&0}+spZ52QB1 zZAan%0EsU{n|&JgSo_LhWQ=`Xu%q*-{3Gxl`&rZn+hkdS{LdY!FBD_dpU)L@z<&;{w5y$B+Ie{0Zj2 zaN)X;lwr(%JDuKDr^j&1(md2KtU=>nJ^BayV_dB8t)hvii)tQsp*wd7X^A&Zk+ zS5^~4V$CRL3Zh~27XSl>KHL%cRoHaKxiQ9^sTs(x&}!uL@v)L?bLFY#6T>yB+k6=K z%i`~aR|zJMt4kHDurpdpzGM;%W9Ci)`i^Vu--kc7e}_Crb!(>hkyFEZr0Nxcl-i7ndJ&p!P(AVNQ z_Y6Ed+^M7VOt(5!Vw9QsXi;YgBt$%Hp_P>6Fg*x8$GupF0;|a4z8Cmg@yEno0J@4R zD}n$b_nw7Z&A2I$$zE$|zmo4!t#D!H>KedmYx_!j$TyywNh-%I%SeEV$smiV- zC4N#qwQk)5;wHk9bCM4xmfuX2%Kl{G3Fl@<-5mh+Ca>9eUtHF2VM{$LP`M0wk{fp_ z0RI4M82xLS=S7IDY)p}|0%YFAva@F%pnWNl#>@dz(Q*M9$K~{|N$~#w!LJg@jrwv~ zq0SoORb9V;BwkW9eyBPBuJG;&qB%#>$E~>IHZ{t>D9PA$E-IT>drm zcD1IxI4YX258b4w&l55qxKj8^xfk?HLl=LAD zRcic*&YcxK8PRxKbMV!X;90!<+KEY5vj00V>ZE6cRj(p-sqXYQcs|VZ_tY)!ZP<(GWMU2+ zFgVXnJJv1T#BUghNGz-gJu}-i%E90@x1CYo+Ck@v>#ckr7R1~JIOGb!;-LY3Mo;Y- z32if8pD|DpaI85v_cf;;oUo$|?Oc8hT5|YU$81(99FDjwc&=AfywtQw7+l*6h=<*l zKfFGpzu{X`#nYG3&H;KGpX>?98D)4QOh;1KfY;=dXpd z{c77=wNJC$$0iTX3FQx=2m06C-?I|B{29>%nBV4H=O6Xm>$)eGQCS|VMHE)2I96YY zKjaf2!8v3c5%5n(xMGXz3NwG%^vwx|7FjRheM7@dlA`3zmb- zAG&gzaQ^_pN3S)EtvwAPcsrjj{3F%o()>l@j}Kgek7=pO=&W!;Nr^`upE<8mxIi0u z=RLbuk^Dwh@OQ>dD_KHT+g6NNT_!)(+(pwrRX_Ocdc-$teP*(Sb?Trx;P7#urFavM zESyiL=jV)SF01h=Tu8)(PF=VkTIr3(p)~O6I#ggtKuInbaH^ngCa}CeXZ@q%YdAKY zipE3i04Mw_)$BB@Z8p`}A=>N?Nj$cF>$?dJ9FI30Q&kg}(Yzr8U*bkfn8r-NDGKMF zr@v8K*LQK*k1xuO&eA@wC;%}%lz&sn{c3n-TYFh<?;{aEuvE%B`KK-mdAxGf<0EIKHy|AAD09QX? zw2DLsTO%?_f-|)g4&0I}=ik{=!Xv_-7P!4-D{*%ITx9U!<9{{V`$ zMAa`ZAVX*6L}H2nE!^7rPrCho{>; z=u2op$MF&CUA>N%7LjaS@CX?s)S3o`9+he4zxu)}$i6;&S{fyTX*z6$uc!HbPO3U) zsk|uN-rwO| zSHMq&&mJ|cQA^xPcPMV4fA#C8`1|4`29XYz0l=AnY#ecrG5XZ5?5Eir&4#lr$B4W- z(q$ynu8iAr&N_kmSG0I+E~BjIQ!otaIyQUc3}(J@yVccxHT*x*k%rHoCezr9bU>SRUsl>LHonG`u%D8hL*BsPP z>bB=!*RHZmk=!kyAKek6gZi@?>U2#Zbm$ctK{K%@aC(mNI;KIw3_kTwj)CS0Q)U|5nXBxsOmG`U8#BQ zrD^12-JOdc)SCT{{j@b`d>Q*P_}+NV%Ztlo(&53!%{+>SAMg$J`3jm)oadlDJ!-lE zhp$Ejt*R>EO>mH>4Eu{gf-#)dMcueeu^1KCPinz(P~nH`SQ?xJD-0Y1)_^#jT1}8jM;HhBSMK+~ zs1rx{2jF;kRJQQVo_k;mWhTD|_2oMx1aX7Ke(HDv^Kb0$rOtTS;h0AU{+&Rj)MrxK zhx!e>aCbzF$GVE=wOv=rR~xgAPo*06rY!BPV^-v<#y*3ot}n*7a$0GZcPg&#vF_Rr zQb+)PW`P~I#M#=w{Xb+ z02+c=HUvA+$mcohpYW?T5n>kFRE{_eoMY0t+?!`&j8Zut8QL4a8OqoMEv!no909q{ z^Q@`t)a7y0j%$C$1i|8)84oetTD*Dfxfn1XlbWWm86_m1I^b7}U0$q@YJ*Xw7E!f> z%ThM<;}xf8h=vF&j=86V5s}9o@lvd2PzYT5RK^x5%Ii_mLklZz`=nM}`hMg%<#W_` ztyi-p4qJ|c6<5n(yK+>~JN7D_x-zxCnyDYnwCA=f3&h$fzqp8#vKYAv2UA^0Sqh9E zeKFFRJ+xqDvfOv9oLuxq(R{A#=HRsp8X`ycdJgps#*FuDPSBsux+X~b?$znuhSy5bgeafJ)}o&i<^eYd~=rX_yNb@eQCZNyiG!Dz=*QN8XTUXhB^A? zyQxxC<8G%dTD;A^h;D&ql1XtQo!gv+_aJ&!c9wqCscJ_IS~d}e3!EC&@Jh&RrnYgC znTdf>khs7n@~oc&Jd5IuW)0ce`8nyuX@7*rZf_$y#aAV~OQdKijp>_-M_-f=>S;9@ z;)>wM7*fg(2^se3>F-#67}VQc_`l*if;{iB+pWHNAQEzWdsg)EE#KQDcQLRm3FIQL zZhoByC#^WU-HuAuiRixt7>xtOSOArgdVkkHuhP3q>$r6IA``F=jP3WXYvB}dSm-*` zfp9l0j!#lHb@U%WSrBTI__JS~)RAnBkH8#pUtO0)PMW^R_^ifUm0DY~wYk-zv(hHJ zmB3U|-1-4u0qfd@$Hs4t^WGBE*y-m84=z*L+)}b z$-iYk0Dom^GWde_H6#8$32vQ<-`I4m-vHPRJ5P)#Dqq*GE1jAXt!t88OiLDR?oao9KOgB` z#+4hS3P9_HPin@sWT+}v)$09ORH6IFKawW#M~G+AETCvK+q=bAGPID~M;ao5j1b2p zo<{?rug_1~$K$ug4~h0#-Ik4}UU+A~wm-SN`y-z==Lh~;%fVsK-53@6AE;Y-(Y3n_ zrqBWGNBRDB$au%${+)U7_gd2a&VeP4Mtmse<;^S&d@U7fki45#ciXt}F|9XvOHSR- z&JWoK;GK_%HF4YXK7%7aLl>EWjq{=H%^=%TKcXnTH{UlN8>#n>%y1*5z(yd znJm2NftKRsLpYY*w=p|P!oacYI@NE3J_e50MYV-Ywl~^xwgUo=zcC?~*!02dJ)-tqglNDUcF!`?J#nlV1C9t1ZBmNX$)+ zWJcMaY^{9f;;(>r{s;I&;ja{4jry*O;yYWJ$o~MIGG-#6pGGKtxjpOXdkJCGw3wxV znViNP92|~2iu}H^iks!w`?_~=S0awy&7ztoxYQ$myh*rXPdwvsJ*zU~!kR7Qrbe4l zy?zK&bn)c+{G?WlQpGzgQXmrj(yg51w@%bPpQN2eEk5T~v9Y?l&y#H|;bnEkau+$r z70+aEeGU`F9s}^6mjmirjf4wp2ye}Jo=D$tL zaV~{8*!Zko8dWCb%*{iF??`(SZo8d)*$yCMx-VQPNRjZ8w9s;{Exc;@=*}#`E zsEh&$2a20s)6+-Op)x4*W^k&#>*TTdi^NLLc6)eSC$U-{J$2!)B<_uNmGrGW67F3& zkyx-*kTT(jWMRlb3Gs?=73((oCaWV{Un=j4=#QE~wB=tNPy1h=t$J>!@YBOrI_2)CsM(D| z;^I#*t-;J{a0d!F?cX)>zwFMr_@AX*sr}!a(J4G<_iStHeSZG{%f6X2j2wQI`Ho{X zLN{H{v%$sHb|QwuNU(48O)k<5ca8-I^TkeYuue(a=~&6B#u%K6t9!0P5hSqb`Pa-# z65h8x*w9N$8N+$$czxvMQSmg)lRW9)0fEhg5j&fz?`^vN|X&yTge9x%>~>Fy3` z#=2i-#Y+n1_O5$envB34g&&PqmiOh$$PR166XM0~%)44S04LJAjX%V5ULYli2dy_% zvX&Q=?X_)QI3Z)6G269x2gEPS=p$Ksf;OUTSTIsA5>ii@1!BdguH{VHA0Tmo6_(;fI6cNk75TsMGhT)}3CQ634r}k<_$P(Hy8V;Ww>sG^G8@q)PzivBs%{v3D~{{X}qrIgx@m8(P^-VM9k zbc&-Jh#VFNuWIY-#{U3ok-Ok8h(}M}TK@p)M05e?3;S#M8L)rh4%Nm_aR>hZ9H}k; z0BmmpMRLUI6Bd^pRI;r&zp03mhp*(ZXr2u_>uKZ^BZQ}Mrt9T||MdP3C3TH@Ite|6f`TF4FHFhtK zeg%ORIQ$)Uv9ACGiv#}vAFs~e5&U&JG%Xf~d;Oyt9iC;w7I^dOe~5MC`HI5Pe`$N` zc~aW`-U&v~8d;gbx$nRvcL%2(svIKqXwgn-SvG!{T7J4Tu^GB2iL{{Z6a^W#bVqO=Wl1-0F)!6f5sjT3yKILavN$jIZT<6Xai zyjN$gD~nx0WHzOiIOc7#I0S;EbRdjij`c|;qC`1LPVJv!-Tu+u4!MCLo5I)ALW~?n z!Y#QSINyU&Tz=CY4V~N0@U8TWNhGquc_aP$@RYY(m?D(`WpxCV?V7JPoq`T15$ir8 z__^?-#Mh8r>i+-^q|`28j71caMF}W_I8pQT89$v~(?4i0hdL-lvG6t3s2v1x!ZH5< zkJpFXS*bq#jZu4b5)rrNQ-U!-U7tu?e$`$MblES3wI)->(jor<;_H*U_{s2!>rne` z$HQr6y9YjV#R+fy4!lxWf%P9+r!)fx2RvgmXcuSF5q{P_1Jk1N;qZ2&5-7k#SVlkb z`oY%!0BC=N{vnn*wNHl^H_{;tjXY2>2mbr7p6)FEY-91oQ<~puZ3CRLU))29= z&I!YlkEMKXJ*j5F9>0Zl9|NPu#-9Z7$M&Q@)}4@Dp8N6B{t5@+uYx}lb)N?6{u0+U zOZ_v+^DeCZ&*eXv5=b`gkT(IqO6vyNYA{{ZpY`7YbTvMR`%0P_CxD8>i*=B&x#wh=3FEA0%$Ks@`JS^@QiukBg;J3)4j zAHe&lorV@)vs&^G{k5%YkJ@|of08)e{tR5muj_AX$Jh6j@y)J`*E1xt#)_-J0ft!m zf1g_Gt-L(r_hjG#aj=Hl?f7yjJ0aNmr^4U0Z@~Wm2I|eK=zj?Bbd5)0h}>JnY>rgm zmB^Fn`B!590Ps=o216<*{2_iJ!xQrZZN@+CrF>mBidIP=05c!}usAGu7y_d{54yOJ z6>`!R1;)alFMbbPAI_%ec0S;T{t6f1>5*J`J6;NN$!mT;@+D4x;GkX(yHKaXTI=L( z+D*UZ{<6M9UkrVk-*z_@!8=nw@GZaN=}2^#t>;LljpQy1t0Z6q<^4GsnU7ai}0reVsFp>r|q zm`j^G_xMr5&?4SL2PeogrKv`6af1^}2HpMowV2;_v83B1{?|h>S=Fj06pqod(V%lR z2-J}DF)sDqH;Ch9vNQsS7H(;|wX_VWK4*(x7+7B{iFu0qJN7 zbJ$llbNKDdTP;M)J18hX_!5=yx>jqIwF$obb(Ufa8v9IK{UlY`;e<}(H_eNV zn*=+m^Ekr?5mAgtah>Zt_gu~O;9j{G3YeSS9zuBGj1nmzFbeoN={NSN>$yAV&00j* z{$^J_-*B%G-?Bw`Qtq1He*m@zg=^{NWGiIsT9G#EB(O(E@M2jO!Zp3C%$@>s>C6lm zHijNT{zvcsqK35L=q9ocqHgP)@fs#}P?fCBXu^N(O3ex0*bZ|DZ+$Wqmx7<{a zIzX_e&0d+g)#)C+Tpy%7se|~8u`ZB!yQv&@H@vNu@RVtjL0ECq;evOBPLCehHr&2R zdxKU-+rM9FD&&S8sS>^r8>KfA*lV-;yx(H-GDU|oYZb?vF~%Ij(z3G&LK4x$|#<-)~~#LvYuGM0$w4Zjc^I2yPfAB~o?#hutTcKe-m!XKWrs z=$mik1V4KjDix^yHcJc?&oq8fJ(Ka}Za^;4j1V9Uf1_T$Y1FsO_`k|rrT{zj=6kP{*C&lgXph;qOG&#D%ChbwEl+o7W?pRW>sPurJwSY)N#UP& z!Ut6bko*3Uv9%ty1muCMxbj2V>4I?N_zB5vQEt(_`>*aS9 zEC6f?$^xC`CtaIQ>*Fuivp3z*>jXD;E-Xm)@zRL*npNKbjr8y;A2RN2{Y?Ni18;Y@ zHLo+5o~1sldaargS4qNE^Jp5;Uf7|{9(lj@cf-&`%0!bhma zcWK@wb16Q%+COB;{R+#I z&H6Xr*9BD*!~_m?K$e*Py!-X?L40FW?K{GlA7)}XnX9-qQL zITYgwjW9daGsll=IE&GE-xYCq*|7_~T%}WG`X~nuRf3|BXGKD;z}WV&JAA);hD#{M z$vWY^GEYyK!dXA6R2nMc6Fj)kP@Yr@H(gxoid8B9&;Op`o~o>3#;3kceRH%CgxIXR z-Bd?QI$v!%O})7@a$Y#yoA4!;Wb9%D;qfEIuGq#E(mhs6BTO%kWj=oQeVpFDhUc3{ z#$#{8rqx}DSOBcl%{C04H&qIg;fGr@zlsp zCbdEWnS}^aluU&(CJxBMI<~8e z)TJPIjhba;n<65cZkY!O7AE4?z|J2Mg2GdQ!#DoGXyjX{p#-}D?suv9hLmmK^)>~? z!%Ldp7vwz9td-2t0S^>7B^o7cc#O&>s|$`1|;p?S%Xu(kCp3 zd~)^w1Bi8>Qf0I|zf|OwD_Ul(Kt8#|nZ06hPYw`Itm1DOz@b2%$zz!pCIo+bJ;-SD zdc@hn^22Ul*mrlSXVBwe)3BPUDXCk8Y3mW2Hn`8BiANa^TYldb*_zko2o>JBoLeX5 zkq^HrehyOaw^goH)eL1t9s zc{SHbF_E%FknWJU_KsEWfufeF)rFK$)RuDy9n08?D2F28!NnMB=z?(2>Fc5+o=T?lfLaEe?OgN_Pj4`r{(Ev2oYIQIx`;bp<`uAZHq{&)ate za4$Z3{+@*^?mYeft&+TVH^_{s`XfzxQq?@jOMlJ4ICR%oo=Xu`82!bd^iF_&(Ja(- zx^Cg;^U0%%%M#0`1Y+#sY`6CL0LgXOI_3*b2*!X~^C39XVD5iq{@1I(mYGsQq*UIw#`$st>|7EaU=63!pvTEQzVi=$;rfL<9n~8FmKK}h;gE+-q_|*+ zeSa}Y>yt>u9rzZ8TE5sVmy&})Ti;CKYR}%&>39e{T~3~ z{yXlj5H4zq6So<$72HnNjl__u)0TK|O5QcU=R^=?dF_=S-E^k~_MRd!0sbdg#jm?| zxMDrlX4P*+XvY8DtI+*jKKxw}b}L-VSIF-?a^*k3smg=S>6Oe@x$0}o%)V(O`B%$x z$mS?l#SG!{oYnY_-RDBN3gzT(9(khe^%l(PgNime%{DRPy*3~O)e#ax=WcgSAG9<- zew?J)RHo-YbM8F8$}ZT?d=_|)jRe|o<3S$ne2}yZKAlf&ynl0im7m7%*;w;yDfA#O z^Q!F|deK;B{|_beIw9LJYqUWmp8CJE83q3jHoG9@NeTfVC?<2 zXE7=Fmx?!pUODwiWwYJ9{_5vEq>@bSE^NM`Ths_0&1=iqN+kQ;z|phSczQC%%CbC1+xp?(99slsv}L(HsJh^6DvyjfT2KyE zN#9kYUedziC4wC>^BSFm-+(dxp}cg*RC~b{p9G5|pabQg@6YunSy*pfvZM*c70dlH zZyMo&g)v4GA4QnI;o8Myb}5e2?u?7!+9fq>-OcTwKY_!FGeXo+S2y_`M`beh zq47=*T^RN6DL^63rAf`8aO?i;*sR(F{awjrR9~mElY|^}$lq4qO6Q{^RvFL63sdH! z%VzFCH-3O|V@rl?yG_n4V-AjXIiur-{|(cBfCW<`pN&)DflPtSpaR?$(M2xI9jV_7 z-(xzIpCsXr?AcOV`UM1(20=TQ`-%QkXGNxho=3hq7j*^IayRx{!%>GXWCkasXAI^! zH{JLWPG2v9y<$Gm0@qh7LosgyT;hlDDzH8&UR54e)b@}~yU`R)W+^Dq$7?1JhpkGw zC8RB=JG7Y3dkqx311JvyONd5Hj9fp7>uTRUp)eJBEeHYAEKH2TK4E?coiLUMhlZw@ znDvUdT|#;-6EX|U=427&a1Y#yxcPUg5k zh5^nL3T`xueI7p;4If{V#wwt>od^_svOTQTKu&>OHs3lHv&Ra zBCO0z&@aQ4)nBvj!Z+y~R)+@_eqnj{@Da)_%oO>|KO*z10*19za(*!5-AWZSIvg$m z7p+KCBZvXNtDRR~%nbjDeHu>72Zu$wf|WT|o_r`OjL!@e-#;44QEz^+1pBZhdj}_C z7>4(0aBw8m6#`E$6cjLdO^n5)iIY%&z6&xDc0Li?4~<=|xi}#)0>8x>!5s%Yq`Cv2 zbqI9nKlIrJz4=c1USwWiaF0F5J(%NB&!iZn;0sOwdLF^Y$N*Vj`Y~FEvc~D8d`k!p zRSn0huf8nF{&y6Ww2Dgp?E>=dr6k0pfbP^|v-Jh&(f0IHH`fC$}mz zm49_r-Gj_fD+@8#mCmQxU7^tJo;+l>nF~J83sA@0SmCw)W^ch$dZY zh6xcnH7$YRv*i#nAAK$BYmNSPUm^f0?I`%z0uQ)gDpj1C;uejyEon`Qnu4CnDEel4V+da zC5&Wez6_Utv-Wbe8>Kj>u@gEE~#uw58TH7NRzlfilmW3@M-4APi8sLTJ%1MOZo% zA7zESiU-SVw8bGF^KQ;mIHEE~;NiYX*za=rabsbz$#5IH*=V(1LDZvVl+3Mn6L^n1r#4Pnb8YJz% zP)+U4a^!Pkr%SGBav0eTOKjX6KF%Y9s`UHIhJP#mg?{o6zI{G!YnaI#9hRpz-hb!w z+G9T1h%>Yo?i;E4mG2Xrc&9 z$)jGreVewz=U1rGc*?Yx!LVKZ$Esg+(?mubg|7Sw;&kBxvtdI`0lH0S8^V7;DjS?x zatZ4PW2PT4vvjQ)@LXMe-*>KWr6PTh&|k<(zFaLSrqOIa(>e?j&p5CE{E`;P$g&Gf zfZr?9$EQOE!tP;y3-vPrCGI~(C<>ME46Grb8_b5vW>(w+2cqy}dR1S4x3Hrq4_jfgL8rOa2wOD zAq;5E|7MA+;NA>>5-2r9NsaMte-=U_oZUt|mzDr;fg7_xB&75khf+hQN1*&g>f8FHIPQvEra;P_R zL+P03-d?)|RK9=zLisNP+5IbO^e?F7)}MCB^1GF)?D{MGwpphTJgs{#Li1={vPSmN z{I})PZADq>yH?MWwV`;^0Gis+xFIigRQ{CkgrKy^bvXA)NOTo?gufCm#Qttax2qbavaD%UXT!II92#oK zS*2jB(_WQUex4+TaMjD$;&>@V`ZA)aoyox1*VP{FEcD(Qt?lV4NM|u>plnH!GLi{H zj6Fvz?{aAfX?R3XfM6Tv%O|JU@T9H(lKL@);R@?eC&n4~{gyr^{d_0d1WTL-amc=S z9G*|1n1OM-2wsO}Y`v8@7g?(35x%-B-bln}N#8?h@ZnodoM^FOZ9liz(e`GqRMems zObmw(Sv)d&UW&5mrSLG{b6B;#4;nH-_ZwNlA2Bk@3DJBv3S6u_4q%$$N2{bdK0+1c zj6DF4smG8X;6?-Wqa_@8iJ^^{a9}{A1-j2&SLkXn$I9_;BU33nUgQHAFHR-SBTOZ= zax>RtZl6c0DNNY--wu8=MoHJD31qKC5b-^!?JcYCgW`XZUb!uY0Zr|9<102Zm@!$( z@bnA?{_LuhJ$%G3!4yjfPSbC!NucN$KGl{IS@QFkuyOm>J9BeQoc&X8^_p0e_HiEU zX8^HdrOjpDu}sNnY^5>%=&0svb7Tb0Y;=IeFk;l@z+p2tg*srf6L@jF(b#CogZDOC zuGZsx>KllQvoiB*G;Zo25H+3X6ZKSg0CbEqH#KlAkp1&wLGqA)coGugtpr&8kbT?X z){5uD!{GKf_o_U)a;McCLV0fQ zhksg3&gu^1{NuOCSzGNnvrle$=fSQ6FSfC6p4#Z!|C(%;NaJtOy&yONYX8y}rzHFs z(a#GbehBd$NQ=e-oU-KhAsiI0hLkQU8_s>%OifC-NEj`mx`e9yu4hxuO*yyKy^s5s zI^MkQVVbEbR9aJZix>uUt;>4M-p~g66_B<5n)|nQK^`k%a_N4orQ8@tOQ_a>3*m3( zAdu3=72U>S5j+%&2nTUX8{C|esIl}KH(C0K?sj<($qYS^S?FKv#b3ZwrwSs+)DrZX zzwYNHF-hk@nai2Opx2EzRwr4if)V`CcAZN2`ni5m%3Msv!9G^bNRCp}W9>E1l45sI<9wWa z^N(~e%27w4eMimMyU9Z#Y)V&hEQZ)!0g?NfZQ-?b6{L}uw*bn}*zXFhiY|Q=8M&4a>BmQHP1`AX zx9F)9dkpFX4WyG=+x|4huw%KVs#{FWXp`j@smvLNDrbqIyOJ3UJ* z0Ty5sY66E5pe-O631V0OUBe4rZ>Y}eqF-XB6P|XJ2^NgmutbgTebj@k(?sa2K&J@dQQV^(U%Yx`!`5t zh5@U^gfP-v~-a)15MjOjTqc2L8go9Xn>>W480_n6OqX?A&MeM3H3`sqUGo|FZe2rS@P zx#HL#Tkwt0v6o|tTO-(#^)X_HFxYT-zIq_7PO8%VN=^G4c9-djrPuxKnbL$i3A{kN zt4-DRt&s?1wfQ^7@{pc0oF?Z_X9b^wE=-s-qt9Y$(F=yL@?2_dv?^(gqh+;%jGjYT zK4NcI_gmXS`b(-uf%#EjMIiO`4)Y|T70LebcC~Ao2-*um`aGb@TEmp}>{YxZubOl)$@Wiq8X|RIS%YD5tn)5vS+HRWOcHux51vZN z;==G|g4L#Q1kIUj9~<%wgie>&xfv4M)LG=%S0oV!mTMMc=z-h`i+K3)C@rSDRe=^5 zi%;Tk+u#}1?&lB5-NH-Ulif=H0W7{Y-}zr4AI0K~;KwiTRkCG*>$I9h{79C#b(oW^GK4w^OY4$wpf@UZ|fQ-T}8>D7^Q9v z;DjHjl}3hT#IjdNcmYs3(+ThmKE>FM>7oqa>F#cbF+K8rGj*Q$Teb($ld#pneCh7LySxy9v~j4w(b6BwOEiF5J0Z zq)O4kziy5x@zWFBGBOHBNmM8#?CP75@GvDQOw}lfSM(U;;tU)8 zV>L#yo~QwRxT!Mg_qKDxK5UX}wsy-QkVcdn^;6|8o`02XSLL;m3KwBOc01L@zq^0* zl+jbZ)ll=P^7Iz+t!gG-K0J6L9RZ^%s9a9B_}WO>|9t)1`R5V7zc9FAnO*e_Hv>2E z^VBeHu-Ij#Lw}oB<6m$MjE0!sq#-qDc%xrr$lKxIy2Q2rYn+ql{Z_3MH~cdp2}mel zu+js2m3q6|4L)BT=~c!EqHHv*Pq>k7jBk1R%Q&R z-=a;gbYbfCu<@)bXJqTcPkFS|JI2iLr)w@)T$fc2J40`gJED}KpX^E#FVCfaXJhdO zBy2-rk>y$OP14<sr$Y}F~XCR(-(u4QkRB39oEH|XZ&f<`3Qm^oE zf7Qk-0-kl&yB(XXd8d%JgvtUC{h#I>hPgkgUyJ^jjX0L15@4R+DN7LSqqgQE;pZj< zRdrm7dWuymlgE-#K1p-e6u6!Bo>G+JFq<$AnF8FQby06PMHC$D<&05J^Lodbf&x9u z8H+ah(P9%AwKNJ3-V!YS<&WRJq`PmiwE8E?zjSaeE9|pbXX7AQ8xK>`7_RA(^Hse` z!ok&G_EINoftu5!4=Gj@Y)z(?{5*Ms&D@&s&Vb1RJj5!xBT@I8XHH9D87d# zOq8B0a1^HHgt~>#qMb1j0=ZF_{R|A?zgIr#W1w3Vr~5FZZU(D`1?gD|e`;-!XkL%RZD>ZECKEU!tfzugAj{IuD7H_~&n-zob z9?6aNs*+~R#WRYx<8vL-(vq4cDEOsXXtqPK)adY@-()%U?R&m4r$mCjD0ATVQkqf< ziA2BHd+~MR{{WUMPG{-Lm4&$9l0`+}CVjt5^7-}-xX9&E4g5B%N)q0YUC7UT z&5lU9mMQ`T9v+We;N{8%JVlxJRf<3)qrXkCJ;4Kr(i8pbk8MJFN+u@s%btrfzAwc$ zk|Lk@jO!KKu^^iAEwP>*%}F0?$D`Qa67}wPmz11wl36nlDBrmMg`O#!I8a2r<_j*hQCCHxm3+>6@#l=+L3z%D(8~P0#*b ze2u&B@l5A8jbd?8)VJDA8_No$=5D#8?Y@kw*8tFAJK|FN?AwEQ4Q(fDi~hM3+n={^ zjf+kGt3qrk=k6m6Ujbfx@UmMD%GYz#fy)6Jr%+lxs7f;;gTbEn&hyfJ) z5$7#8uYN}FzR!Ce`DV;*o{4LmG{n+r7i$Dp0w%lnG)31fe0)3xsl>Bz&^TYz+ z+VD^QcSjcWQ9X_cpAg=|ta&adlKK2vNfT39pji)Wt<7*EIZ~0Wje^D>|3DvlS4DNZ zl2W@W8>?h9)P-w-6MgvRwEdw)Rp#bS1oj_(*PGXVV*YG4=JMH$Ls>FOg7AZ+Df#uP2+#mI( zBpWJeLO;g5ZJL+MDOjs>u7>8k?8bVgU_i{OXTUn*zb4L3D$uwv=V>5FTI!9RyMT_W zNJAk0#nS-Jw)$&zF5<_P2Om~3lEtBVugASM?20huq%49@4*Tm7K`eAgsJ|gu#iFt0 zdHhHbMR_n7E%wo3gb{3xN}Wfm?(gQKIJ9NQ_NDIMZzc@Ik@Q>1GWqXeyvcqyhZ>1r z?=D+hF-4$*gybN;^8#>)6n2u)_iyye$V+iEt!7lSKu7t4dCN#pA2$oj~k z?weO**%IIMvp)ByBHHp&r`~4IP~SQwF;vRPRncsfYQtO(w**jj%0#))y6$=9@@P6em#|J^@id&b39+a z^3B$3DsE0+7*qI6rAk>j?sq^ELiBj~veZC{mFb(3#B448G+nEv62))4Z8Vp_GCsv% zmA^Avn5+8R6wE1~6&phz6wbcW*gyqyw@f~B6T*Ye9_2-%@k@AAb9k_})lo)4*JjOO zGWI9BWB>^_8i^{UMGDFGox4E|)DGA{H}Rc8xVjOA8YKFxMq>Si3po*7cm} zD|z?1{6-PBCIol$-EzS(l5=u=v5nh}-I5Gv^Zgp8;JcADh!1)^788y*J8RG&J6wv7 zonRndF&?x*x~}PpNVT`3fw!|R?;CF$PeEbTgpx>c!x{EhbrkA-PH)E&o8ezB&L=(_aRZ7jDZ?#sGI@%t;b}FhoFm2JM zKAIrL6QPS)0zV_VWKqP^jB4*BLFZ-)@LcH*xX~7{ak+C^hP~>6DdnunRgooasM_3B zQRT`keqKu%l;NF0yu>kTLT)aPb=I8jAFznm8FPjoNJmJ5d#FNiaOnmT`(fZds|d?T zS{`Ef!NkGR*3Ixp2ZX{GrgLjF28X+-5Jpilvn~=4LQq;nLp<-F<<*;r>ny;~4$E`i zp&74()kfl2SY>iunkJgZT&m{{Q|*oy)b={$FoU&vR7tFWK!#o}+!VY4C4b{OklX1a z=BhxPqtp6f9k`?OD!vLOUh#*Rb<6sq%a$g*{eq>h?R317s}%3;nC6O%OM?Px>!T1F z+QHnKs>`m5r6bD7(8IYYdP-cqSbDK#Q>=w}D3{`;hwjGAmX|IAF&0JXX@T9Yt`{|L zFUwWA0_^PM0p$p(*8lSLXU3Z%%HaUC@MGR@TTX?Pxf24iW{>t*hnQ%rlVm&`b{WK*-9=!AL2-qu zl_nL^--JXNgRX-^N*U9fX-P&2b2_}MH7<0ro4=nrStj$kZP98q8R+K$5_ZxhQL7Ao z<%jrhb>J<~b8zU01(SB8t&Z{V_BVfq_R%A$heqi)NJ`1&gmaS0$InDbbRyE?$ZIf} zHE1^|0BCbZjr~R;UfGxC(Tj!lxwE`g-=cmdhn0oIWVFj^Vu2wkOqifuW&~H9z;Cav zLI94@xw;cwRw7*THBplP!RDeGR#qxpK6ey2fiuWrhpGj65S zMb1&uM=VTwWNI!TfvJ1GA1jJGG+2w7jq)(`hOCk-g?0my~DCssi<|Q9pL1 zF^S?5plHor=G?9>A6%~5^V*qGH2ByRE;*l(;=B`YitH6#Dy-d3z-q0cze~8p1##I) zu;kZ`crf6UA{h=;Y+zBK)5!U1_<~&v%*a+Zzf7asylnzh zX>W~E(rNdiRv-T{R z{jZR2E*^5XZ&*78Ec5Lqx>#WYjySJP49BNr7$koN42RMeOG;Py&8K~w-<^(&7b>b< zg#-I9kMCgUE#yht%);xmKXh->H+x`TOi4D^i5O>p&&v9$L3U00Mg9#@GR@=;L*z{N z9XzL<4D?05rlz3bNd~nH_%*P3luJ%s!!xBO^^EwkCrTAW50^?iB<5$20EciLA@G|6 zOy8>hNoqc|m^+ys}9H4`M+BaKXmM#DNkmOZPcn(MhJwYhh~mhc=210CE{YgO|<7o-CJ za9Yy;-%oaa6M~&Md$f{9B+KomF#_-`w=+xeKBh5*H2&2$GXKDaBZx+CXWJfhIO#_> zSBg=^JA^fzzP65sg(X-`*1{A)K?+!AMXgKbBcz$z2|>Clg!#{yqk*(i67s8uh`5Se zu>$_`Zv&S<5aeBY{AuC}A2t&F)}Kty<|ne`PV;)J}bg z=YwD&!53N?O05>3;bF;`D(wePuy4X$*6PZG)?t$r(`J-2|M_NLfEF1r%VmAyOjeL_a|5a3a<~BzeN)d+0^H`959=BkD;yDe2tA z?9^g2j+H5<;GGOEfQC?IyCh@4!QPK_m$ln^^+rk#-n_N^Yx!qo#W`-7s3`dPXj9-k zGzSSMwcB^8_X|;QHIv|nMmFjC^ALR76T_C?S>_2>;E>{8eO}PEN;haUSEy(AL=2n6?+^ zXfaMb*E52LwJKTrDL-`%+De*b*WN46zZHyR`PyxslPfYSt;vrEc{+jV??NA`o=Mb|YeF@O$|7FEP7z;Hr6Jc?hnH zfz*SV3EJ;Q+p@T&>{+Pd9;T6W#szYH*<9bSH=6GAv10=W-Rh0Ul%t+66<~;lh zHa)2XN1!0Z1L814i#?Kw?l$k@4}LC501xOtK;n0shZ&S$TUtq@ZH?$%FTy=)SC7HJ zoHMz8+m#KGu{&buBATS=2+_Mi_P$ zKK>OXd5|2nbb8mep0Wo=UMO&5j_XAB!m}$lFvTHh5E)-R|z@(5*ifdN; z=-Yrm#a{vX&xvLOOZi9M?!O!|WcUk86BCpwe@4;zuStNAW8%bFnaJ|24sFyhzTc?5zw4Zcaa)3FM#%P25A?xdEc#mMB zq%5CIXrz-MJ0$}swLH&E2CSC?8ryuHj}Z_nj%PRGpbug`LE)hAM(5|96o1-k%*+-Z zpBqn!u(B!;7a17LiTX6RL!Du7WK#RUCEYtrxmgDgJ#tlSqK{_eqXvdT|?2DXmlD7ghXHCJFoN+-3ZwbYgW zYVliWHo!ZCZPKTIr`j(KLDrYWsT}intOi^0KZ~@j*t>Xwu3EHOJrJTt>~Ra{?_TCu?MX6MkH$9s`>Px%wAd4?s32I3g0dMb&Xm9qg{(a*jlAjKX(Er%E{~xYL4v zxC&!p(YBdau}OOCdr@Btw({$Lda_OorHLAcI3)Z;MkpcsuAT)i^5S;NNdlHIF6 zsLHm6D_>4V_%git`}%U_G*+RR0F0#$wfH)l`=go#s`5D0a~H-*OoaYo)qb8P9G>=h z$X0Yek0w~<#wFi`0C#naZ+ZM$9@07&eJpLBK}boh4-U_1EK6)xYGtsIXc8fXK&^?5 z!W1b^WyU<-e*9KopG@B6Z(XJ$6WH$2`wqh3?>~QK_oV0H{JHhW?Pfw(NSV5ZftQxB zx)TklUeUslqJqD+2z`ybzkJ(K#X!a5HoQ$)tq1QV{CP3c>(EURZT|RjpqF|$|DuA) z;=Orazm(rSbWf1eA6qPP)#J(^<|`;c&UKlQ!10^G{Fd%!PuqI21q-dnsJ)xMo0OKhC0(R^5zqJia?S0zmjY z5(=QE4+DOaDWX5ff$TyW(=FVX`UCr`<40;q3aGp%`Wr7IRnrsWc;RU>le?5X)%29& zIJ5|CIi|2DkcI7aE?F|It`Esj(^lL8-8=p7NR^r=pdhl%35+; z2iT@FUtaJBw!wqMO_hgU8)1{=Kh0cE@Ar+>g61_@qak$cBLVW;ww`WG4W(}GmMGdZ z<~H=xwf!pWN;&Do;Jvenr)Qy8Mh4CV>w*_$v=7z1^OL{G#_}xftVP~Q`d#pUhA#}v zz&v(1@&$S0p}@X%XeEd~L5laV3%?~DgRJe2~ z9dw!^*S2;y+`Wh0m9|R3kM@(ZEoZ!x6wNd6Skd)c7tmEWqQ(sxYX+V(A#9k0X%#eC;&_#|bH zS}V`e3KP852x)YIDqHi33$ESH!NR<^%NDQ{aCLiF$#R&WoBXF4I|JVmSnqU>}<5|*O{OwRlRDv77e zG~1HAdO_o&;_fnA1-xgy$2X^jbVO+VxK|xX!-raRzS1dS8i#s#c%>a@*5P#u)n}4P=Eh$-bj$NrCbXTihE(reUp%vx)Hq0 zZ){hmz&*&@KoPCcENAj>snS+oQJesjR{{aYT2+jKSG6M|f zEIRzv`A_N8e`0QCV=*x9c4Y%@cP?XZP2|;d2V|HS!27vv4!h?NI{t(i?b*sa_Pdge zgxV+8)4c693m#z|^9!bzLIve(AHS$f%Y1m_-89v2Uy!Ju5I$FLisKtx zig1LNw0%^fjQ`Vr=p~U`rR!HjHCj6UMYoR9yf4bq9tuAwOsAdEO1h@YERP}GOC$6s3uqs_Ma~i+1 zxZv`*I_%X7W-Z=Qr~%p3u8>NIC1brizOb^5aB#KCL(sl_c>mucQ;M#n&jvr#zw#&I z`2d`-o);)|X(#amCAW>X{Yl#)ST)tDQY@uYx3&K!jI}xO5gQ9*f^5kGl5^s7Y=v>h7nta{5RAu zIB}Ph6#=SSW?06b0^$`Gyk#4Y~JgD8z{hyh$y$ zA~ywY3gW$*fC0P7Ux{^edL>dVw`GiKQ>DYpSt-VMs41b>wUg^|h@+I!Z#|5f{}{CI z4+2`jDrzk~1g`wcxhkP@HLoDKw!>JVH>FloL9f+71scq+0|sgS1GG8pb0@eC262FX zr$jxOOWX{lr`-%iFyU;yLTlL{m+*p(I_w1}mii@aMRr0R2y7;F}2I+c5Z)F z0&3QY9>8ONshV6arO8bb1{k!}qCK@#W7TvSnMF?<9^R>zJ7`D^r>fT<95!S{;__Wk)LA9N#^|`21KzwihVK9=a?pX>|E5WKz$Sj?>##}xnH91a2H-+zWr zZ50K-w&$;$tQG#zq}z|t6d{VyZ2nb7lRUvlA}1$?d(a7Ob3Za~3c&=OD5aJ7<(1Cx zW=#}}V<3j@{HTxf48u?RVlpdm&bPajNG!=o;nNgk%a0s_(1Id}rl9S~kK)gTgiE%^?N9w<`l&w%FsAA6}+>T%9TFS$=UbTePIKdn4UHmyb@jg6X%v%$usl zm9Dfzqz0X8I0O6VG~lx5`1u72T3_~L3wLO;t`A|K(hfK6{4u=Gxr)j5Pm`5xeOH^K zl8r)miBm=%K(AJE2HVQnv0WII)^v3~p*#HfuGRC>Z9LcBiPt>B{FbR6Jdk0H@ZJ;i8-k>I5&FkU)Qq5C+59{po{tj@WG8 z{K>7lVQ)J755_R%O{{nCl%;ejj*9fJPwdTJf8;#b8^sjS{^euFSx0zXMc!*TCg-pv zDRsnS9XqMNi$9X2iOPS2zMvx_^pJCKSxch2YQ)c`?#v$OCuz81J-@5_YB>0N_HSpY zhhsR^BS{Zcvi%aCcbA3I-9aTy)VTyR0t#G{bqy@v%}8Gx8(h#OQhf;xU`iIA1bA!8 zAV%mT{O)^A4EGk#1)3er^f8l>oRuMp&A-p`UMi-e#>bC}Kl00a`_679dkeUrNHL^{ zeI>JnuOMgq=$c{|pNhFxQ92WhW}%$i6U1roFMkSu)vnuSJ@h;_JGn6awGYGfgzej3 z|2$5BZ2t#OL9o941O1Xy%lHrB^~NzJ*Z!1AUj@w>C_)^Mr&{~p_D@p30`vfS@45c~ z(upfM>@<4)6j4|d73Ti{v@&n_PpmIYydU~GE7B{@e`p+k!m8Et{rErha#CP?k7r__ z;OCBOqqMdS7y#ononsoiZ3Ohr2(E_843X(lQF6-M06;&9>sku{RRKu{9V)e|6$i2Q ztw@vw?r0Gex&hSl?^i8=UKD;*f&d64WaoqFS1n-1NX9wlfu1k>S7=Xj@c8O#*cN0f zWbmPg8P9HUUfbY!qn|+2<+%A%?9u$79R0!973BW_8@xkft=Z~-55=_iT8-w9J^M6U ze7FQ^SvQmFSB!Mxy?4P-wa+UjC8ND_2@5j=$DoeJe)4lMsdb*^zX%G!>-F=ZRgy& z#~fggNXN@wZ?u#bDs3LLX(=@+B>Nmk?8opO{txMs-QEZWv37UK6}ulQEcF1Mr~Ai@ z@#$6n0BVolX;$(!C0)an86b|;-TXfIfWHvmTd~nCnncrNjwigChRw_g$0ySV@vcYq zk+Dr9!E5%5h-98)jgSn4KIhi6nsZ#sRCGc-wK*rF?eacI@lKg(szSbGNiG063-c+* zP-`|hrJmg)l0>_Yy3T>?vA+0ss!p0yTk7_WE&Ll2$In)i3i60vtQB<&3EtY_anY5qNc#1zr3rGJcTQWL$>F>EuMb$lI8MafpDvyfK&ACZSG@MNe0j|03AOH?tUL=l56*|Nivxicm;Zs z&srkn{nBMl5%-v%7W_22=fhVQ1S2iov$HovQzEI)wiwr}{?C6CH63Heek$-Tp>Zwr zIw}RWo_RdRA#kUh3=T#B;<5fG=rGUV?P|$~?#-m9Xg}Q>zok(9mV7?9KNq}R;#(;i zZ6sz@ zHH#k-yfja1`0zhEF4V?P$_E|#nziui5&r-SBg2dj{J%zjoiH^1HP}Tr#a(gpxzCc! zqXVQ!KDCEyY9mO(#?DUzZ*Oy5m&J=lZ;9IEu0tjvRR^g3(pF?Pqs&pXWF9faan0GY zraKj^ElO+wKwt?6-`ASaTSinabCJLRRQ7hE%X8bG@vARvOgo1|(C3p_6lcX5QX60+ zIp-Xjm_|qUu>EDU~iaTw{0E8Tl2yML9M~>rk z@cqD%(PB~{Ce(N-) ztkL3svLoC0tM-i6@8L^@wz0HtE-9R_jOWV)0zOd1O98>>9TZpS6nq5$SHNGe)a^gV zPZZn6Awd?C1Ir4QG6`MOvpMKnXi#y;#t*;fEHU77^sD8)OD(LwBTCN6U(fR;jaieL z&(v&$@i^PNjz_I&i4}3qF+pTG>`it`Dp9j%6lCJ=kCpx>{58JQ_38CZDc;&<#DQa6 z0zo-eBZ4~qe^FdT-;Pto5GA&+Z5m#{rKW|H10s%m$oS;sVUYFq;E%EO>swox98Rj+ zlzAJ%SAy>7O6SC^x3d`^6E9Y@oen)iAqr+BJl2clrJ!)PhveLCMmuV=D z;g0y3jIb38#F6p|Wl}lDK<)B|u18wcEo>~U;|Ms;Z}VSx;Up5z|9at}D;)9^nrc$dTa){}pAb)?>JdDuHzOLo3# zkbq07H{am4Td4Ze!>H8KTmA<1DaxO{7oeKoh%dY+D7y`9f2PjvwzHX=%T;myt&$;~urT` zEbpQ}X1X~i4!*qrag1Y+Q-^;vPZ~a&qS1(KY4=hu3V8C>iOVi>LFcbQ*1ctgzeADN zR@C*M9eA-XZfqibMMeFzt24%qB#Ls%GRO&B5CFg@oGx-f&(}W&ykBSHeJvoixi57D zYG38rO7=L(^y}^`^Oobp_j-nl9i8kEOEh3y>DSJnnE(L1WxJ9A=ts@d8;yM_`!aaS z>h|gnCu(71G0GDIBo#5R82j9V=v7Z%yH1mgF3uUa&qRH%<;WB?nPR!%bD#04$yP=r z^&fP8RSt=N9;2o~a~R=(QW$a$KT5MCOA-gpS3F>In&(FwC{7wUn`quUWc2l_uks>f zjGo!XKDDnQUoXrdxZ?(>&cLtU$v%Up`OPt%cg1MD--o^n1c8KH=l;10^2CTJ*_@o@ z`&X#^R$`t3@JZdqzz%!<=vS4-3l<}DbHJ?Y{C{y!_)B)N7j|Y)KpEV4tE(VWg(bIf zjP$Cp2EfPw;;!3Ue7V|2dCg#GT8;?zqh~A+K}}mY)rJ9V9yzH5Y`Z|fBh$55LR&cb zj~xJ{2A79m@+FdSmfL}|cVENt>s=@I)rOH6n^L@r#X65Y!j}3kQ}|b&>w2}uk7X2= zm7y)>pa^5S6bekXA8=>-t}d*xdcO;z6~y zJ-5w)*BE186!>r9e~GQGEg+t2zqYYE<3`I2C_D`HCm?RexfS*&fPNZlH#$y%;ncrq z^?gHn%cz*tn4nM#$+YlT4Zvq3C3^E*`HmViTK03ine>@mTs?NDqUPr!BDDTEMej zpRDq3V0~~v74Bai{v29-H`HX)msP&hAk?6Hc>{dJdSw!iuE#FH94uuv%R)mKj8e#^UO^uRH**|XGY3byr0E&Z@YWx zW7pvL`)Q>#1H^B8uU^hKd9z>7CPr{bEH<1TyGAR%(Jg#C;;la7{{TzXFDzz_B$=#4 znRE;Him5!~10x?$D~xXpcuQT?S5~)%`aM&4eh}@t zw$`R|AeH13&2^p}zSqJi>5@wxdk#Gs(8B$M;{7!HkDaB6$KLau*G+Z%&c@=#=F3LW zwM$kC>_H>zemJ0Q_n2ewLDWid*Kohfs(`XA}_^o>$%TN4K$F zGq{XoRu_l#Snb=xT6+jttu1b@96-BOOL=jDv}ASN^}+hqK9{8UcfdDkso%jIO?!DM zx3>xiSr;YW80(Jyz*o&urwG)PlIx|9qs?;(ADitLavSZaZCORp@4P{4`(qqkK>9 zy$}6!HO`24GVRC8NXb1o?Oi9sG$XO7ih@OJ-T)6n)nOE`uq6n$Ja6|gpOI~ znNQyP&9M(XbDjqstL$IeZ(MB);TMSHjz)rMV_SF~dhTZmarhHo6#PF`lUx(rDiAh1 zasUy+3+Fh%EXqIcpL*z`w_(uoKiXRMO?Sl>8dO*i`KA-FV{nY^{{Y!R{A={@_D%R* zZSd>imYWb|Y36}tmR-A5asj~4LF#*+Yx5^e)1&dv#;Z$r0%YW_(fmyy9OJiaSL^Pb z;Y)b@F=MCQ+&ns5aH`D$95lQR3wBZMTp5)8`gB&wU7p4Y9JFUv+R51(_rDZ;AEZm= zTM~o*7#!oT)}UV%cx%K^w7PD!X>->r9Kg1HG1skmuZ?vNhBkJRX-#RS#{B}y zKx~tYh9^IbeCOgn0BIH%4SV5hm9dr7xG~90a^U{{SCB zr07%4ES_G`uqvGAAlJwKI{2d|r#$HekC_?cbM>#I%5b$Dy`{8AkD6mCLO#vCS$fA& zZDZj}N*$WxP1FGk(8b@6_D)p$SCshP+BCU0QKK&Fi8k;s%6U2Z9P{XFu<#FvF5gMl z?BtGEVwps$6M?)8XY%Lpu5(^=y3wcI8kP)_t_cL>5Pu{7d9SvLvG8-VS`YBnruLV% zH&Dt_NSS1gU_R?34)2Rz zDP#WtKVv7;_i0~AcvLHRhQ)#C=Y#&~ubTcfBR|E@6zyUFx&;3K-?Xl}9}6Y!apog1 z&pGtZT1gP_iZTZo=}n2HjH_ok>6!yEkT+AFmCyschAb4Y0Q+X9*dvM16PzA>DGA>q z<2(#!>7Bghyu(bky3*#o zyu9Z6cM=DF2*AnQ&F_r&$o8*CZ;jp`_?6*Ubg9jbp{rX)AiHfs)zK~h0B%`Vs5t0w zYv8L#+s;lg>VBg_Usk6G$@Dz(Z;A51jqLQ@2qv|89E>3nO|ls!JTvF;+P$%pgPPRw zv|8+mZ>xCWB2TlkeUDCtQ6QF9-~a}95^yui5C8xUD@NAS!}>L;d&zVy4f>cgm3b$a zW1{U)=cwqz+|%c?xAC3Yu7}}^xt`t=6ndPtMTN2+3n0$oNazLt^(UG=ii=i_mw)pA z0Dx`vj(y$VZ}a~Ef_$yx9b;A0JX?2bYjGk^BY9K2Eu0?lDIIWglhZlvUeoY*;LP48 zxYD4RyxTi=+-=#(4o(T&I}CyTNv?{=;Xj7FEbINME^TK20G^k&QbZ3t462m_*c^MB z_aA~D5z*q*9_vKCg62o&U$acEGoRuBoPId3PE}vCT&l?)QlynfDM>c}00V8l3|rY* zBpX+Ae9pmnZ*QlyXI^*?(gbbM0HAa|7ykgSUqfmd6UC13N+=K)&+xP1rV?ADVBnm;keUUG9;^Z1X& z9x#_|4(k&iyAUF+Tj+i*@T;xSyqHDaIY~9`QiG+V-1BQzb#+PD*zs11_PS)UPM>`O zbKjcrttcV!{DIgjT-!-$B9Zsml%PM3;D0*$3scuu#eNo!8;FEgu`&|CU^vevzG?V{ zBWQj;kRaMtM4LZMbpCbUX3rj^m)v=+?9xbVCoX*SM@Bs5O1ls%-2NYG;OpKR@d}ZN zkVc? zG9~jAX8Bs*IFrrq4RGTdO3C#x9&vG++?9#%fC& zt9?q^JG*HF*6uQ_r-MkySm)Ndx78fBu+Orb60OE7?~mD8N_-E{LFyjo{{Tn5d=gQ% z@J}6ZEAL;~P!aGuLC+_B&;E~+qNc+~u2Dr5&QMpL{CZC_;eM*W?ZN*5qf)&JxDSrM z@=Wzl_u>Bl(W^;;^DdWc7-OLATUPe%9!_#AHoy!G-D_&!EW1Fd8Dc0)DaRYDLMYh* z9eQG`!mYTIj1HBhY8911<+IHL91xx{^LGcmPX)G9Ib`FSdMVxx)4=uZQzT>z4tI0x zXaj>j30b}@YdVza{*8U0h!#fZHkJ$lJapUn*KhFZc8|lFSDH4-_Gs2XJ1|fW@}p3* zd&>)(Q74xq(X?Vr<6$a5Kb|Wq;l-Y%qxfD8J5<_r7&iuO+k-CiwX^QHubad{(yZ4< zuinqJ!&X>~G-UTykKDIA&1M+yEF^Y3E>3+t>*N0b+9Sua=~fq3wv1I*rW^IIskLoE zqS2>}uo(vc4sl;H-FO*1ckwdb3;S~VRjB(^$a+Wz-2{3QT=lq@boJT|UD{isJ6>9Wuhy06fFCGy{x%dja|y`QOL> zAlHm=S1q;8Jiy{+0HUM6P{~#O+^l!N#bS9qL-hk@|TTmHD3gLYq-|# zL{}QjGGQcVVIIt2C`_H84#48Mol8%=)cj31i0-Es6Wv_2w?R1C#PfmZE7U$A>bj4K zHPL_KO&N68x*K2tglA|2``u0mKDC)?;oU3yKK|m{Q8IZdz(z<6t&W6t=zVLlDY&cX z&o;H`H)VBxhOUV{xVK*{-~qQd#})K%!Rt8x0I_AejQOp<46A}L2OmoLdqK06<4b+Q zOM;=-Zy}WR`jKB&d@+yvFT#s!9@w3R;+QxrK|j4WD|hxc@P*%m{ttONj6yrrk^ z(yvMPxHuJE;shLbuSoF>=`o&hpGwTV3f%`z!nLJBSoBgmiq4$_6V5;s2N{{X^$se~Z0F$^BV%UZyVJg`my!N~8At$FkKnbRGSW-Fg9 zLhk)Kel&vRl;w$Vc-!2c=}krY{OZCeb;tnw4(6bu%vR!7O@IL0<27w8KtMxh z9l)rgWs6|I!XF4c8wCC+zJt%ZbM`$o zoA=j+NZb@)kf4>^*uV$5ARk{stm+Eq7(7?XpYTz?gy+UT23y7&be9(T?}Wo$LeMrA zOJ-&BRlnWZBm^D`pI#he3CTvL%%v$u-j3+-Z`teim+;?(yiwx)Rx{$AS6^SIpZLJe(ihqjsE}z47u=|2yX24q_#(3tKuCV=G?MlBP^=>Ph*lt z9ep^@hCc}PO(=MSP55!;L2i5nrO9TwDwh*Z%JNF&b#}uXoc0|6$DaH?{hTyycfejR z)I49RUcbc4d*n-99$UY%86gMvjIuhBB!>qBH~&38djsV99cZ^-JDYVs$&{Exf- z3Vzu>8TivD*zMCf=C54C$c_?|_!GY~|4VZCed$o|j%G|?@; zv@KSBKg3qB$#-dUXCn)U_AdMuQS+%87(SWCI`;k&@bAapi2ncp?*1WJd{fucMX_0* z>_*~9)OBrW3!A%%L6TYdF7C{EDlmX#^$%Ww;7{4VRQQA8?O#}m=-4fQjzzQb{JE~x zoCaHTB|{ZloRi7uE2f?bivAN%8jU#u|U0b>!O45KJYOz^X_K><#jlRXegfX9K5N!M@Y{SK#Irm%@7s zqbZ6gr6+SPP7##y2e{}@ann0a_+@#md`Gmi8ef$=S~j6Qw2|#ZD&;q0x|4&)1p8M? z!_cSiSsD9k^0Xq}y$COSaei#2X8yh-71Zr#EUBpJIl22 z-G#lz_RRM(8PJ}C_jv=3PDng~^g6yg@MYDqU9zJ^fI|=n2iNegCXo`x-8VwMX)Fn0 zk%8CquK3fY)#9``>bkI%rq2HR#d@Bjtw(N`?Ip$2sxh~;TWkZ-f{gUr-?wh{^;hiQ z;cpRXo-fo>P`5<#H$2T8K2k9_`M>}GK?-;sLCt)b@S55kZ{pvAEj*@3u5V)ui`9T9 zf%O>!>tC(O;@Qf~KWQQ-^a7KSMb zEVxqTIR&wtE%Y1Nmf!gImb1_=_w*x#L+Hpp)VUqQ?AzZ9f-m9&34dlF{vt0 zZ3L`?kVvl$D;mAZcT;UE^KQps{OW}Al8?Lv?Zscch(;P+yN-Gx{*^}Mw?%}>A-^i2 zBeD3b>Yoq15xXQ51OEUa3iB9=AdpDxE7ZOyF8=_Bz6;O%^BsTdkgqs`G0#l&`Kv1b z03X~{J&7PukWNE(1HEWMeo#rz&{bPtyIH>R9;2mPx5SZrr>F4Zxy?x&>}=$Mc|216 zr|eeqP7urGM$&moalZhZel+AIm=ZmWSc7YwxL%xt(v+^#v2bZgIc;-=(EcS{d|L2K zmfj%n=+JF0WoV$hvbZkFxZ^n-9!`HuSDJh`_%V6m82m|Ml1X~;uxnW|O1KAllb-w@ zmFiv_zfXjI5}Hf9VS0-^$dO1%jB-lz?ih1gzXh-E{8iyQUlLwg$7&_Ln%m2XvZ6F? zs>3|sAhK2a&E@9-fg1*S_w7;m$HKo5-rQK}nl6%x=WAR>3k-UN{W@2&!|?74eNs!! z8v5fzn&FI-h!G@(&#uNC6W;_?9dWgf4Z$>*J|{;|x!)d{8nNfDS=fF;wWg$_d23^W zRVYrU?xd1^8h2lEYx=#B;$9B@mZZ0yZEwf=?(0a$n)a};wug>J@-fG@YukPi+Ci@B z*Pbf0v=(|OwiX&XgxVy5PtP)r%IpANP`U44FnGJ;4d0EvCFnj2)2^q~?=>r-ZzQ*_ zvItb(SCM=+@jZsWrx5bIHvux>NI?46LLez|50N~Q zv2LZZaa}cNR#hBoP3R?G3ZSP>p8ejRg^yMlL<-Iu_rjevf`|K-Tiok`)Iq#2Zhr^5? z!ump#5h${N2>T%N*N?-cOzFwN0Q**r-QAx%Qe5+LeOX#X1Obo%=zXfa!mFPxzUf~| zbdzoa8P8McQLrPQYDQ%%i&L>w5wslh-k^rjw`KZw#cCa!R50ZFnuXA_afKM~&S)LZ z{{Z3Ak>L*#hBzB|KHgcZNJ_FDryzCtxfQ+e^*pZ#_>dEmwCDc)n&)j}C!&B`sqJ0g zVkU9jk22!muGYwpac#L=XBf||JT}(~6`Q_K@cm6qA_E=)CGo~MqS7WZNX$x%0IAlI zWRXaA5L6#hJ!;E?94{s?RB-*d{{ZXMaYl^gLBYq(pGubMLZ%cL*cdThna5B6096E^ zGk)0`)UfzVK+{pt8cjiNr4k$g6hjI1%aVCN!QQ@Ku((?t9&5Q^UH<@KY1?aU8x>B> z_XOc{)13PA>VLKtxVOGMFc}>AR;?PKA9n$e5$H)*KkzK~uLbd?``Y+k^obrRUMMX} zD{dfQ57>5L;VGcWvUQw3AtTsdl&SJh#}fk~m%90&#I$Bt>0cIj)Am>KUySwpr)?ugwzry1?|5JXc5-ur&2!Vl(S_;Mg7rF<9<1$J6&?E& z{to!MKONicRzY?YKbD6o!_|BK2d7Hd_^>ZLDW*#`!D!g90EZOzO4S6%CA8XGKg6Q_C;u~Jc>nk(! z+r_>)gIaGcX$zvZb^u8y(;e&2_1_a%Y0@NLWr8VWj7WfqhoT-zeaym>g~fdpqDf;j10elhrKZ>ee%Una1H<(JN3C8CJ|CnZ4#?t{otfHHB4 z`+8LAQnYS-eR{I4fU&!4|tFe?;dG6`RALy`Dry>H0AU?2gw zbM>zkohZt>mjlqAIpVWs4CEYSjs`ka%ca~~oaePLE>1YeJmmGP*vp<5j2&*xn;8yp zNas6EeA)4=hWMl6W#|pq$sPXyc9rzUhZGHV*Eq<2-M&*_H2i8@{8RBJK*72k`}t{I zRDKd(=K|_kv7QI5OA77n_)w{}NIahPYAC>Lag$rN0>cj2i?#vi2dOoM;(HgqyRg&R zG8DVdA~$`5a}t#Qq|;@YaUC~o|Z^Zh1rvn<5Db|zIU&H#j<9ktuCj3uIZ56 zGrL{>{!pmS$8pC!0R)x7JdRCxAC98DgI!}GRJpn)-qs>9!9Ozyh*_^-oKW0~wNS5SZ-XSXg${{VRu`&X+` z)vlFmT^=O~(4i-Wy{**z{PE@2$2oj&C9%K0z0j87<6D{9CrRPm^1DQFwC%=KK*7kb zZ}?Z>`@8F#>(3Ecy|~grlHXOcCJU*e1FS_`%~teMPEQ>4u7h6F{5!2`g|%Oa7qP{= zK1B9X+By2}iA{DB+jw42hnHGMg6zNHAl4m`?e2^-JT`M71#ah*s9muim?q*~f~W^P zRO&gTxoz?{RHKJZ({jH?R+odzYghImDP=oqkb-JH3{K`f*B=P zV`%ala%XB1V`H>e#lI1JeXV%o$CsAcj*n?&JUdv6Yu1`GxR5dOD<8Vq&N>SHLGVYy zs~>}30JRHSXk<&vi(xF!J8qed+zsdZ$L40o@jF-MKaBLTY2wLsw{Nn+a?NFM><8|o zFS-`bZ=7r=u$SJts999JmrV{TiF*g^o{Cm|p4a(n_Z=UFyiy=v#4o4Rt)=-%Xlsh@JDb#?f!9G?y=xacU8P(kHd;0W1Pf@6n;QgLY+JN z>t9nhhOGVQOHS4~Z|&LPw=JgYUV4`Q09AKvlB<8TuA3VN>5=BbPMEjHixC{xw!Qg;-uco{=@RZqZH&)(V!zl`*1d>m+eCzQR0igK9#5U1oW4V{f zSr>w-5y2piyO~emJ?pNWNXfp(n~0@2B)YTD{6l!RIyR3#%J&gO_Ka7nD!y0$075mn z@S@gTN5qzgJ3$QY!>~|GAIiD52`ms>DhU=AW(}NRo;uXfY8QG$ike-~Nl*~-N07yi zGmpxuUh=Xzm$@!>ec|985-kJ5wxUzz&v1()q5cv_Ps;=FuQTz##9J%vPg>F~rCC-T zkcW-829urG`gAASyjE|CJ}~hPlA3+zh;HXn0+>_?!jF6aYR`gvJ9#C^iW_#gx?{?Y zaqdrQij%Z?B05yBFKILAkA?Q%X3*qN#H$sMjPaJqjwJ z7IBpsK7*}&;rlEhkKm4ktOz1Yo)7(ZdMa!}J!*<5u400?KaJx*4Yf@4-4FhaTJI}_ z_}j^%8 zsWvP_9Au8X`u>#`x1z6ybvu={W?13IUtk-Uj=&GcKJ{z<6C0J&WU+`e*E51QfxsRA z0R2_b89k%1&xn(M6}=J7{3Fn{5#pq_nqNNN-2Cs1oDPFE^zVl+)vuXTlw2;{X9J(* z{uSrG8}NPRnckRT6R;yc&bkg#gt;w_ z0Y1K!nRb4Dx%U;Rb~-Toy$xjCjyiOpMrF}CEPB=7hvPpGJU`F;zNhu7cV8=WoSMDh z1^)nw`@`oy^7^0Fm>oC8Vo$^^O+ngEm4^QSwrf~6aG#iyxSn}6)O<^YX7T>3xv&6? z{{ZAQtVMt#h6JDMUVQ#0bghd~Y(RkRQ;vO2EW{~h89R8!JJn@X+qs*8_eLpzwBIY8 z%j=qfns(9vh)>E#BxBx{W_e^~%7VR{k<*Hxrwz1>jAJd$T!l9P*yE|sdIVWi2`pga zVB>O*1z`M7u!mLf4~Q(Tqx)UFwsNb$Ir9;e?p%5ik@(j|9Dv3Oj5c}2NY?S*G}iM* zWr|4rwgUrj#&J^B(NT73pF94;+S=P`SH1w%7+d(OLbHzE)>#*wOGa5_`!&>AA2?mc zC&%3=x$9p>YX1NR^zB+kn(i?nW4mS*l;^m}Bz*y{V@dc4;oW1v+9r#sG|=lh1hTf5 zt?AbdZGC6C*nDpbRv1Yitomx2J zjeD^zk_TXG*Zv87Fo)pZ?7QKg318a9CC#putA7z(i7q7trU%#Nb{|1rQSeLP6dp48 zlP8Y6ZQ~oSiMsxSFoxD!)L5)+B|MV_y8NocgPeLENCv*9@tQ_-36c0fGuFDJXwsJ} zzn}H@M#iBjI3X|Hi7m77vaAt}_B9WZ3 z$-p~sew6VK!E>vt!>2TH+R91tB`nAfuF=kGpz-&?n-7d09=fpBJU4BBrXVs!b3D6c zL+YM~r#0t35BOu_y)xQcPX&Bo)Z(>(7}m#87W#wR5OK5_qjm#~V|8Has@9a9pWu2h zjOeDR*{;{v6*1|6r_}|8V5Nzzj zcxGrJ&@@YiQWok62{T-%U^0&>z(4GtO7{N%6#N45=Zo#W&Et<4YCbU1avn`CdzH1Z zl!Kq%L2i+W26OVcBiPjs8F~I2(iX-?ia6kp%D1~3IJ9}uOfASEoJccmY#~C0JwT*v|?k=9di}MvIa85Zr zO=;UAgdt7`PEA*aJg!_8Bky`*tw8_~ZWvJAGsv!UKm!WySB!TxJ*L?oV#Y=~9@wVr z4H-Db2Y!a8w_vDF3Fo~6D0q^>&sEZHZ0{p+XE?*kh+M+`1CTi*92|XXq3{-o{{RT5 zg(K5$e3r9YHdy3?g=Z%tgU(L}^Q!i(Lu8 z)BKIp)jDozYK#8>vY&*tJ#WR4`1VN(-A6Y2ZRkkB1RVNq1dqnPr1**Pg8N3$t|5K) zQ*Gi${{U3p+3bF`;@=7WD|jE_=Z5WV_1_cNXlWSQkvshFfs6$Jl55$HyWt-m_+TZT zp*+yspfF6fG6ZoZb_L#;Y~hIY#d>(FRIAN6zFn80glfrJ+Oy^RzaDA&M!O$~d{e1g zT-!+7p|XMe#+Z*lr|$Zb$0nD?e;h1)W8p1NNYFIs?BcmY9PI>HV1#EG_vwM}Tb?8R zoIE-%Wz(&V)$Q{)AjP$V6V&m=Rq*%0JqN-b9GhRbY4wY96w*fxxWSQPQqqJifItHT z{RMgy>tN$+Hrm^<72$}I_LH(l$#!vGcwba9+nvfj=@|;@Yt_61<4avbRI?N2H(6C& zbt{uxhr~~h`WM6(hfC0W8$OpDL}ubykmHWwM;^U<)`!DS4#_phxhhs$iK0co&JOOQ z@ULpRQ>D*RHfNVctBkoK?vK$8E5ypz_7;0bl_UX`v48-_LGCN&Uxc0(*S;ovNYt)n z%$D~zcMj7N@~KG-OvlsYz!mG7T>k)S@r~Rtj74E>6`B>n$vuCc>t9M)=$2YYDPv`C zW?1f%?C~sN+q*UZ$Lr z8P6cqG-9qx9Dp%Yd4nZ^ot&T<8ToorB7+i_`B)6_e>#-NrcJrVM;WMG7C2sqwmMJ( zP86IF2pGpWG|&bVsW}{UsLPK%0UNW%;4*4LvZRA@Yy;Dr(*wWo3Ekl@5^NYdPB(MU zmTLw$-X#oME>s2!oCDm7===bxz83KZBam~B-yy7MkS@@AcNN|CB1Cs%Rla4<%-B30 zfYPiamM0{SPNJ0zc-G9z;pgCG=QBuL47bhDeE`L5 z=$;z5(RJ-&@W_oNo0y}JG0c|?pfTqM?=x}N<@6Oksc8|lw$mB#jHYJ!a#-bZM|^O< zi8bF(-Dx7^v}YmvBl)^V?IqwVr8pCPr3fH(54ZBcuh2Ib4o9j+n0tG_CBh7k!uJ&!WqydwepA-tY29 zV|LcALo;#L<~=Ke@yEnHAHzx-?&V_1#sTYIOXE+CiJ{yy6W=PiY%F{EC$OyV3V2gj z@%Fo8tzRH(7$jLzDFDQWImbP#=cig#bc}47??VL)KfO{{vGmu2HHOwS*e^s zGA`Vy=s@d_t$APVd!P#1j)^9ZwxAtG)fCJO`tAoOpWj=1VPJFf$FsyP$0J z!xh?pI`LoHYvW8eLR(u^E~Pfcg?TyluKJBCN}6|i9)1#(<%#x^k1SQs&s`Gg1lQ%a zmkQYcuR;%e*Qm?jYfVnW%pkYR*R6T~0F3ktB(@r~afol0>~6S?_>o)qPq?o@@UM#_ zIx?V;NXoePuWGcU;-^fEJY&x3)cGDW@dLonX%g;=G8hoqJmijQhl;f1yoTa<_Xw`7 z{NM&p&Y&frF4e3oN zi^{OhVBaPTUT8NOyPSLpf&~5;ft8M@c?iB6empS(7)0)U; zhldDlZqJ@_cppPwH2i46_^aYfsKB}$pZeyt^v{PNRn~2vJeDW)HS<5lWhdgNi93I# z4oCfSO6sNXkoP#BEmZH$K{YgLxf!UA7>+VJb5vZMY|>uO}Tt+DDpCMbg(j%(oHjXB)>PMsd(EzJJ_X}i60Gv&s(+Mtj*8RNeOxu1hx9+Ts(z4wUP zHL$qTbxoFtScsMap_K}c;@TUZ_N&dO_&IN=Sxa?e70`~>10?SxnFYHjOmW+(>}#w2 zoBlk_@CmiJHC-TT8Xl#IF_l>%ofit|r|&6Kf<1v1VBSn z%DP%;pAPOV5w}FTgwC1l8wR`28tO3HSi7?YDhbIruL%8&el$VxTj9rvb$e@BEhDzo z+T2AZ17pfY&IeAlOXKIo7t?Gm5o8D#yMHR#RCMU7EoynR@XHg8l~n!I_xTN*;#b-H zK(YO-h}HYK!LOmbEedNIHKq0R!bnaXV|U7obk2L%=U>8a4{HAa7W`P6gUK<|VUzcJ zNdiXCU-y5VeNpib;Ny6w!M3)y8n&&bi#PM5I&JKh&zyA18qN#Y%I#eBage8pQHqx) zyV~#cJxk+Hi!{402;EvsaEvBg5uVlXFNyp!rg+VDpX}Fyc*Jb&Z-Bwb9D+Rvt-snI z#rJlaE}y5H+t-p93^KjbZ+SNGtjsZzdz$%5!^Yabhc51Bi&U0rCIl)F0!N?jfH^-? zUX>L((siDlju#48N-GYX`oB}#J{EXp&S;{0OWjVz4>_~FWdqx5ZeP;9Qu+&vD^ZUb z>u6MC=Zejb=j2y`d=~M;X)-KR^KMVxZn^cZTJe6l1?8YvSY^4$tSdr((#KXFRMkDL z_!cbuDs|9qZ*{$6Q;ar3Np>QP^U$nHnI6WxH}-?@Ev4S7(?<%zAdMBA4XUexK;y6i zzK!^Q2HiCybIYD9%f31477*&!T5Qn^jp|IvpW!RF2j8uFRQ=r#8nvf4W8#Rl2_m(= zfulZ980@A8pZwo4_x=~WwV-sJM$wcmVEh9b7s`f4uN)g_W4!xb3-iuf0W}O5@j5scCXmc5;#c+>DOIcdvB#C1a?i zzO!(avV^~oCA!L_>_MJchyw#S&wLzJLMc0#RGVv-=eVWE+U??pGhhk6NONE100J594v$@ZVD-KYkvc_0?;gM;Z%Gh!7Rer`@G zSOLZ{imeL=QIUWLTDb#)%z4|7&ViQU5-=Gnx9L{ZN{rPtx?QQa9FE?VaU=}bBpy17 z002;1B#xQQNUR((umpZ}5mM!e;Cs`YY)pj&jsTzzC&n{eXg}#Ohn~wja=9iyP)GHw z9}oDV((dcca<3p5P>qZaLVc^$Zj~;rC02|b%6K^IUTLp*Hp9;QU9oF-Vl(AqjQ1lo z;A1GNa^{ay>2NirS{$!*c8RIlPZG?F7?3Vob9L{~d;b6`@_&e)F^blCMcG8N+ytr@ zqJVJUu217vnRQ(;7$EyhWbkl7#(DbWab8RD8qWU!S&@+~Bx0;iFi7pksqNR^v4r`w zxz#ATdf4$F7V9g0uS(X6Jh&unp@!V|$?xg-S3}@EJ_ppJnq+5C*%AfL?DZJ~-2E#e z4-VZ~UA%KZOvR3OMt3$(f6u4#uH(c09n`I$C89(CaISE1^!#hB$}n0St9enzf zacs9mD-v*^WP`>t%|FUF*JIBZiC1w#zk8elPv^x|g%;7H4DBqD5X5!e?f(GQtMXmQ z)=%<=k;XtB04LMdxm`ymb9mBGiS&2Fji2y<=n^IneVn!jPF<^cj`G+89Ok*dg)$`H z4m4E^yP}1nbqo&D9k@P+7&!N?iIm2N8NlG0`WSpD`D%;bm#ZQxw-_VbR8oLXx3xZB zm9jH}I*O|)Culh%tyz%`$RS2KJ@HvLu>%=pay_d`;zeL_oQlq!w*q~5rUq@p;E;I+ zu6Pl_@&5pa4srgPpVqUl2?X=OHE+NTkBB}UAA2{^_3hS}9dE@eke?8>WKotLS0Hpg zQrAA0ZZcS$_UDS$_^~oC#9e3{?okOHzvY@%9MY%R6qEC0a!(&x;F|ZD(zZpJ=4X&? zAc4+voC8*4Tp(iE$OGl;?OE^_F$ZE~3`x%b{{Z#s^{M^Y+D_5iryi9IWuTj!9ho>7 z&sv_^OgPBKM^Y-9$mQ6o;AfycD$1_Xrx;`2kc-ep>4#IsbA~wvtimu!4EQadr>Uw@ z%I*sEAMJFhVwl3LN!)#N){q$9Ht{{@h4o7fQWLt;MKR7j2s|Iwyzk>b#*usB!)vEJ ziFr8MrZdUU9YuP7inR6CbSa|)agQz+87J5A$MUZM@n^$!*Q}9Yn4yigqr`C7_BF`) zAv?_;-WpPz7c12s*YL|r@gIPG6k184G-FN?neE<8P?#e1Y{ULVyY5JjqLmaMYb zv2Cg*DZ?NoM(_avvT`c-#OVGpUFkOy_{-rIove#x8*eP*SynyVkGlJa_2RlIL0vgn zr{`m((r?~vMZK^3cl*zuygmDG{9n|x>2zxW9o&d47Wc>yQ^sjLETcK*69`L1( zt$nHei^S7N*AwR>%x5K=etM32SCd}rUl6_;US7=K3GK9_Xo6`(wq+J1Cmlm`$RfPY z#=o@x0E~4FUQ0F8En?IoVG)MNpOoXF>+4-|q0gl_q>N))G=4d`KO}vepR^^-r1INp z7YTrHdBzQV&-*}r&_8XwmfFH?*~rSAll80*4){;T9}(}YA6}Jo#ByYqL(8mV?{m|h z20c%;c(;snpX}{_P=$+Zf!q%;<*}caKZR|F!%^q%(T*n-S~Tw!Wcu|icrMoW$Nn+X zw9)h2Y8P?9ILP|iCM!1kjRPIxbGBb~_y;Yv&Hv!O*)6<_{#-v7V)&BsP z+{nKnJf2AOsA0P|HpVH~7a7l~#a6qSJoY6M2zCz;%{+SB%`(Vi+RZ*~=#}(dq-H-e$PXwL0%n88%0Iou~dwviV7$<>T zwf_K#_Zn09OGJ?q6bsK|QpVfSS0m*ebH!Hx6)1ULxX&i6#2HD!13dD3*EykRL}b9u zbHzF+$_B{fcEv{l``qOB$3SW7OpS(eK<0rKN7vG-nY^;9q>@iT%?&5G<0(bnF2)_z>zikd$!YE1Z_UXdao6z8eDV8I zcscKu)5LItB#`{bz-JtDUqyKLPyWHwY+vmQ{i8evTZ;|2F{VIPKI9%pZYz!PMTA}@ z@ZHUXhj77mP1zu0Bc9(%@!@^pxhR!9M5Bx)1El;r{@PJ|5FGA#!w0e$1AO zQ7Ps_D*pg-RL@MFqXctbbNnyV{7YrwOFLa}O4FsjwnSE!OS%2Tg&r%wl#!^n^*1Yi{;oa5<%k9yhh&%|9*!V$DdWhD0HPYOsU=tXr)6H>JO zoV7{24p>TaS8HCUqIiqq-Nu=#>dzO${a*TE8i71h+3k~IYy!qyuUzxfHS!0<{{S8Q zLimi9`doGze}#0V7q*LSYbm?BnJx$$S@5ca0gsR#ze>;XC+#Dx+Rb#9T6)B#cfV~ay$8gi9rlmn*a}QLyjxeql2v<-Z-HpgQs<7-_FB4b?^^J_($Q} z8y6$~5(}2|uGc%31ORN0J=?n7Zavg>HS9kMygMeF;VY}Ah^58*CA4R5+#ta}UX|Hiq?H>@-LrsmqF!8IlP}d@TYbKEzFtTIv$y>8{qs}eUF9JZHQ^+C8UrJatRwfv4h9C zuEpPa{DhC|UQ8YJJp4qjJ9a8a#505=c|7}6aRzkB`^S@?C%)pBQ6e41X7hb#zOK$i?c^~Frhxqeb|m<0Ew zbPFzD<^!H7#g){AV}d9Hy6_r>@VAIDf=cxt?i$LEZU`Wk9Q|usz)|e*uDk)k+J0~N z0jyS3LyUaR2pskAUH<@LCTn&~;6|#Efs6sur7A>Oj^-yIa0WB=q=fmA0zlpf1QWpY zsp3GqDZuB0>qupYfGkvS-F<+sof=tfVZ#Rz z6+(cVDl2{5bP7*arya_QySqHA#QMtI>bEy-8d+P#F3US~!Sd7~8Dri?0ZTVPduFh7 z8Rgczb8!;$<-?goYS@hxK2%(ge}v~JllWITW+Z(xPqy0gYBC{lYJisox@Xf00q4`& zx<3TYx+Tz!B?9{XbxEbh1dJOmwBX?tc8;8xM_y~tglvkNyRqh8C-H<|5B@WJH`D_) zygGXMmlDhvGYO?_=aIkz9@zwrwfdr()xV28GY!fxK6E3Hax;!=@jK&YxSH?8oo0BH zeVHWtGGOrNq=3Wg&3(7~6MoRL_@BaS;hj$8{{U*~iX#l?{d_|KTzifI{QK95o#7=q zQLhe~Guz0qQB@^EPj_|e)fPN`V>f_&X|4F4_d}D!k;in46{-SSD`f+7BKKm%pP;X% zz8e14{{RH_KMLC34-&S9gAlx0m4wikWWXjiAqwY^cs&kkeLuri`i`acn~0T*fJWiL z6;n{~cZL2J>+)Ym3>sagrEXGKrnVDVUas|TDn-G;1aRCO9A^aAkAs{mE=jL>Ej2!^ z;eEYV1t+eyTes_H`9G4>#rVtdTj7t6G->41{CT2YOc9JRd4+fX0JD;{@n?^GMXu`l zZPm`DeQz8{1W-7+Pv4^O20_W=9QW^EQhZWB0I%fMqVZ3KAkp(NekW7fTj6e-4c*8YUz zFm>tDQT8ZPNhAH;oR+32%5eT1$#^*jpmpM@8@yi*;Mmh$cps9oE0kC+d{1NhZ{ ziJmbYBGnDOvjb-XADDD@_4*3N@KxEc@imRkPwwOdN+%P4;$P7b-(zJog~_@@um3tfN?u!T0b?O!3(pc|-BBp^=FBy$X@<`ByhJ zvo5pZ2DDrw&cq;5fHS#x&rY7=y7-NYzlIW6%RvR|+_K0CC0$T$Dmmbd*zQI<*F>F? zXA+IwkJ7*RC)TI-zl5GB3+6O-`tvFoS7S08c!)cD4DP}1FnufNdx;Fv@y0sj*P8y# zo)?3{-wm&?U|_a-&Z5_ru_^gd*<+3f0Kx0B6(sj8Ytj6JB&1~E9tTWUhc|g>btPmH zLMFfbB>t})t_sf9jO$Q`pwy8z&mk;gTd%X%E&@jtU%a9j1-Yv!+v zk+=LU4-+0RZijw<)unwY;qo6^v^W8`e?wn4{Afe}01H3FM5!a~ApZd4i(OQ{5?<#B z&@$&BkiAVM`|^B<UVVV8=o>z01AC^$^0|kyKfOlJVhh< zTarl&DmgzYld*3e@1nn`u>J#&?K>eot10RSyD)&~Zf=@Cc>UuEG zBk7!Gyhq``jcjy}7ER)*u2$Mh*$g*9ScMTgk_ZRW9H>EI^;0z zgWj%Fl%F?KDpb`uX|q0I)P6L4NBx-WEFF9UXR7G;j*!Qz8ChbDjsRH#ugY?J@O^9F zbl)EQbnykWQe1dv!;nQR26v5Ql!QQV-!{Sy57RxX=q)e9HdAO3*k4)0cV{dDDWRDI zql|J2o(*$4hlce30Ef2bZ6@me#wCh);zVygIE1(@fZc%rfOrQzxUWH{$fS~8%;@52 zN^Y8hl)7L1*ZChRd}@CcXwPpCh<+bMJojLcUHPYkbWyG^+9`RD$_4%Pf8)_+}kqEiT#TTd(=&DIHlFi9V5YI^bi0N2Q_D?<2DrDzvPI>ZdF+(_J<_hNh3uW7Fp-P{WTf1}!{ zNY~sBwbN0jB%*mxQc2yNw}dVQr1C6`BZk&I$j5-V8E$>6^QXqY6!o7Od{FT&vtxfW zHkY?g<)WOgmbnSR>A=t9Ut0dt9}tJbAB5MIRS4RukCqU6sj7gOI*i!=$kvym4xMkptfPGK@0ITz@n|}>ocvkmK)U-A? z4JMwqa>VKP1CoSy$ZRmrUe&5;oN`h{?||v2>OLl)P}J`&ZSN+StZ6b0>I$AgJPhL> zjeS>c@V&CEEDT^^VB}ZK`me#gOT>0C_?JsdIU&4JapY-?%eT40u*o3jBiPr!cqYo? z$HJO?S5YKaD-aSaV*@?TJ7?0mDcv)YrmE?hlO_f;k(#8@<@l>^b>hT{k(% ze6o8Sn)}E0Spa+z&_MqE&;E~k_(-Y1I6U_PzV7{(20jVsU4H$~U;6I#6?PguVu~oP zVuH9Yjz98Ebx-%9{{YdeUF~pR9C7~u3fEN6P0;@U=+&SPo9v%FboDj0YDQPDHP6~e z6P?)^t(yi`{v)2lJt_ulp*v0n20GQ-cQLPK9ZqXB$`&>N^Y2#5;3@uQ?|v;`yXf&A(Eo{eetW}L>GarZ|<=xeF*zr$b^TI_dFB8b=J2sy@k=k=<3JhvL6DRwyk9oY8gpL*B$jy}`l7_4M<@(_n& z#~fA`x#FEOMiLdd{o3Sgj0#lKgTMZ?5^mRx{vGJb-$th|jgN|N_cnmcP) z)Vs?w;XwB$yeC!o%q%Wg>6&w1T{+nn{IO;yfE0B;fLEgU3-)pGkH$;uZA0R1{Q7>5 zq&!|8g|;(~`fHE7{_o!P$4c#|hm}To)vLma)a}1yeS1{#e~x@(uGoo}!P3qlx0X;< zCn}*!C_dw_zANfWha=_A20K(*Cx$f73HWx`N73yevb2Rnam5mCRmV;Raz6|{CfNK} z@T2PXahqF2Nz1Y+CaZx^ArB7=&BdKXNrd;vuRi%@0 zILHgn)}-INsN{NcRh@QYxIVPVD$BG3$sdJh%5bCs!RI-v_YAl>{Hr>5RRjaT=j%X> z%c%kqG4m1W)~tL#eEdf6=skYj8OP^TuG=FZ^V|xt@brW6AH#%WCi*|?Ob&N|9+{{R~2BjUcSfR)IEdmr5;b0TjsloHH(WS+Ij zHSZk@V|6E2iXDI+a7jG}VOl7}Avne{o;y|rz0&L$$YIVaUe;eSF`hsjGt#qYW~@<} z9PR8mAn-p5nTu@zou}K8RN|eYBa?&9MLlKn3YBre?N9~9m!Jfb=xIFt$~eb8>ba0J zr#KkxP{>OVG20yWphlDzJC6==jP=EFn)QQtUhwK^8JkFvvofH`w_<+wKe$iiPp3|r z(Ij~oL=3IM?NO7Ov#Dv<5L>#)L~80o#yQ9%q4qt+ao4L(3zlbY8Wmi*p|Q#QNbt44 zkGufTS;h_By8WUC^U%Dfo<(7N}7d@ywVH^(>jW;a;g)>tE*;M$-C**G9{ z$H>4Oa<%W?1eq-ETSt}lBZK6IJOTaR!?kli62D|W40!(HTi4%Xs5=%jL*#XE@mq z$>%*=^sW!#UV&uVn%zlmq1m#4ozCQwmM6LWE9lP<{=!k|I((NAYJPmExl}2YC-bPh z1@MB;;jWv1u6Tf`7Qne@I0udZ_OC_PrwCdGb+HtxS~z-25&PMJ;=dF_@c#hAx7wA_ z5hBO20sHOf2jgECYrZ0v#Cna*okKIvSf9(PBYF{7g(j-$9(jbtC(GCOS zrUiL!gQz9Pi8QvC0^U2QNgaZT6q@xgbbXXLrMo^u9f|g{a8ryi2iGJa(#_pL2^sYw2*@*BkSq(t($#KQYJ#d ziBo~QCl%th+q*K@E-!FMQ`LkxVfWK|?E zIK^PK<9}*4BrIP9@9qZ}AB_nNrFzW6b29)z85|xz&MAU;@KVQ@> z;D%hWJBA2RjCzdL1=hW89C<3Oun4zj1y4`$=uKKz5%iCYn2&~j1sNopbk0XV>P2x7 z$XWX^UI4{*o+WMH3H$`*vVO@QIP3e7Tt%wxkh7h~vWn!ye-WC~_)7@6VVnj$W8SPJ zZIBp+&)v^|dX6}Xy0Wg`ItsK^h*oj|2Ll78bC+^kRr0tbZDUp@0umS=c&LHE0X}AK z-oHxS(>xEX>!5jd%>*Z;*FPuZI-0c!OJqxFZgY2+WG~1$&(^&|z&-oayfg5!&qlh2^6q1ObrIaER0!1i&N3*{iKshExKEcB727f@`|p3cf5xG^tk+4Up$4c~lP8kBG$G}{$$NA}BAzn%~lJZyedj6-{ z(x-Y!ecvq(tHQcWD|0!-Yvvuws@UTlas55(ufOmVu zGm}c3B&C%VyC0Z)ss4ta;-89l`elQiK31QqiI6cPj*KzKrxnvmpEFiOK5Odi&94^x zFYrx-j>)81d7(*Q!zAN@pHrX4zH0cX;4L3Wxhri9FtKa_5E$d2;5(IJ zVYm~?+zxU^e!s0@zL(<980tXDYdnp?-WLiv?oS52$~b!T<#v5+pPre0nJ`vL-@K%Kwnbq#t za(8EE9Gvv+S^oeLHEDc5@TbLkrtC~@9U^x7*^q?%`OR`wsqLnr7p2Z-zSNG>;6IPX zq2c&tM-cC4av8d~Y@CkV5nn{xPadIWw^5MM$f1B8N40)$e$AdOl1~~*VAGh5#kiOP z-!Ayb9Xpb&dU9|p?*9M;Yb0q>26xT7bHA<_@(B9>06N;OKVwnE@@qvsQPs*r5=Q_Y zp0ypkf4s*`iky_Wwpn3p_rN{rk;qBmNj*V5sT_kPA|eR@^ZrPtGOIZ%{{S)S2SH0Y z+0HU^fHT^d8SuZtN8S_xGRLt-KrPrcK#mKx1~I_TT4lj)iaLz&-;F}xqaE2f!328H z2c&ojiSW;e2XH!{U52pIHdWdOns*Wlb*+DgvTyLOh2D+Pl8Q zOxEmJhSwm*ih7@Vu<{pHC=Nz)0OXu>rUQ)aB$9bGDq)niNd#aV(i<`SPp8eTcyj*6 z-HEuGHo}8~cH!_(VoHJd*TLVle~cdQ;tj`yY~y)i`(!T#u~5qynG#23Kr&e66WC;T zHToM5?(WcxU@&fegjc~o8ayDjpS4Gbt|SjE*4j*07FOtRURF;k7tc(Cv=4uJ)}60* zR9WH4s+)ahU({@-SeDGRAKEu67T(=96v@X{IV31N;11@qG(C7hcOIf7ZI)?2+0u0; zRfI-ZGaP}wNu-UKcEa(D3gmt*_?G$|YU4xPmiC%;%iF_g7s&#;DUuo zjjxCvdsu=rzFpkXglQz@f+r;P>f=2!a(UyAS`fOsFr4+WJlDhu$*E5hocT;Z^dO$U z(z`!{TD|`OhxNqNblHqImePktAE+a^JqWH}#ldIQCY1o>mf&`7f0;GZd?d@?I3qYC zIPX_p-p!^gCH=H)eyRKd_^oB}L&GqV;tfLF1)c_Pnl|n|!R=m^;;k)wL7`mfmngH_ zNVwR;a6gB){{X7K1n^#?f8d=`-&xWmXl7L&WNnbLFK|VDd*EM=+HZ+;+?KCA7eghdwxgh)TJp|{iJ-A@oV6&v!!Ztn>j9xx|YJtm)bL)3FjHFAx{L& ztZH9py|{EFjlp8UJ-U-$fB5^v)*79x*>o$8qqxO<*A=C$*NNqsapcB$U@>0a6B#*1 z(pz;k#p5xKJg%#==rZ5Kaargv+NouT}M%$Nzx=MXAvnR z$bSC-s0aGjs{YVl8{jrmcx%IR??N_R-^O_NjSqiz`~`ff;Izzo^It`Tr6>E!olnp6 z98SK@57me&)}1(pa(0Gh!VI37Bbuz-9DcO>UM5!b=Dk#S2YI7-ky}@tUvTr&?1YoJ zso#y+&!>9y&kre^#den0Y33_UBmuU9LPo*20pAK3kMXY((O_xyOETCS=2CD!+7;=V z&x<3n@pXmj4Y63=Mp<*!ST6qn=0!zKRgt|nZCU#l`#9d+X?_H`@NTB&T}Q(5eT`pf zQ6;(NCjjzC-of<6dTOo-c2GTyc`w0>h4BTqguGL0a}~tb`aD+mW)csYRZ4F-3Jw29*L25=5DoM3}iAVIta91Z{{ikVh9P>(Ovbu^l~u~BwupFU_e z7dn59=F(s=Sc z9X8{^{vfmQG%4p;PQu#pO9ADQq$>|!Pp{Uwd;9MUL#4xgbkfSqFxJ-UQ7#xZ%bNAn3^t~TeN-74!mnovU;9ft!sDMc8ZZo(m9iH5*{03uw0))Sm*Mur@vy~ zk283yQjfw~;t6K5wfjw#?s+jQ1!$Zf?v@2lp(C)b2+^Xk@ys{re|a2iw?^Rts8K39 zh4K{kb=e!LoQ$a*`Iq)lwtWZog3+y%kgsib8B%%Kj{g9N2AxF?M%Me9K}u5Pmfg?S z?KUXxY>=S@5HLZk9~pQ}wTl@e69^EFSey#tbUz(jcv031rFpdW`;sWhkJ}x^VthmW zpmdu{Ng{%1-cI4pG5A+PuTG^qHL2v&!Qv@mF9)Y{1I1ngxYOp=?8Ce8%ghui;4d92!r$rs2Gjie#@{wScM6}G{{X;y)lU(8Muy4*4S?RjW6g2j z)C%#B8TgiKw3+3Zo>v^R9&6J}q2o7gS>nI6H;*p-d*lBAv|P!$I21<|YxhxeoB`=k zd^L!w-Aj*~%;0;T2lK95#PNNrT)Td_HQo3D;?nKQw;;?M4`4DsTvv0_2Z*0FR?k!M zZjBAZa3m9NiJxxr3I+uR4nGR-J|B2(7r`e{oEwXo50VQG1Zp;_fPdOzex|x_g%Mj` z>E`l#Xc?_-nC+Bgl6IA2pW((pKIXTzonKFi>PDY7wiff5N(I4p&&e978Fx4bXy@+w z(xn|P$iz)wl^I_Sqiq*f@fM9AHjqr05U4p+^A~Xg@g}<2eq86jU~4@&;BrcbkY74=z*e=9amksQ}#;;qzpYg$p}9x z1NfeUxgVMu?vZh+%C{F&-s%i~^ITjx2kLWM8V$|mq#`)2l2ui}SXXL~#Nd9kSPrXP z)b6}RtX*pw)aK^y`ryqx@(v3V`T>D~*Z?c;pV&9!D(apexcGCbPyYZD9T`m8W5{`$ z%$$@5xs0Ft<%gww7pGp0Mpd$qEZgH_F3wgzKo4{8{{ZW*gF*2|sqo)k(tJ&$%2!g+ z<`c%_q>4WDZR)I~srEHuKVWYLGprNzl%N)*+--JYeDe6hLIW1*%r;u znApbWef!yu_lpx;D+9{(dLFyXn~tmA{12;sAAZc<6Zj*iE%L^?--=mq+NHvA4o4yc z{{WU_{iE|AQPR4t0u%OzZlg8xcf$Vw_$X(Fz9wo==zcNNhl4dqSR{9;F`G}Bj~HfP z8XWqzSDsi`)w(r;#{#**C!CJ;=)wvbMDc3Wl}F7dsNH8-weaSTeXHtIEw-Ph!1q@Z zIlx3gxsT*4^Dp*x{im+J7I@dhI*rYfYB~>yZrMunbXm`ta8T;Aq2MlZuzox_PoS*ZnUsbE^y7ijuifNxo(RZ4%CYXJP|O1DIL3Ww0)^A#ARXED ztDg^CABkQV=byJn$LCnrZpu#}6WcX^;hcrOC3t8P{{S!X{{UJL9S_EKBjV1xl>}lO zf8Uh<02ivKA1e#{+D#ig3ZD1D+b2a;`kr4!1EwD-;OtTuCq(^3egW9Kt=qpAyXPh5?D^}aW7O)UzxOrH1 z2Ltr2Yg;=zFjgql2sp}&AI`mcc^ulkNn6nPoKGCmjn)>6mz&Xkuktb?x44vimgjCh z^q(ljGUrdn&(oUUnn=VfA?h73_oeBjSf>~uSD=Ve4^<&j!bvA zlRhxnD3)@A7|1onhiWq9dmmA5Xx(mg{wn>kw2eA4=_t8Pq==6tk8UgEKaan)4!7|- zV`8$KT`dlN%%3Q8{@1lT#Sld_1$KaO)kY0?_lR^x6CH|heJkm3^r07j1aQEy?aW52Z(M`@S+pMgi_A^V*mu!N~Te$=1DS$({>G>UY4OiMIa$5&juy zn!HyDHR{0~z5FV}bW@-Tz>eFoxO#(Ln%BW(J6H}67&+#@DEGrZ*>X3MUR*>v{KT((|4~$_P{H~|57(Sp^ znO1|0uN{tr^t(NxYqgK($WU7YC;anC4y_v8Vn*8J;1EddSa%n`VM4iNQ;(EqC;HZQ zr+(1KAY44MWp_Ei8RH+*rDCIT-0Cj%G?v~?(qO;ww?BvIYL(RSrOHgqFjS)qbsQdj zG5u=>Ci&uyBt=pLdzr~)QPUpXMP1Yx<0<>|k_!$%$Q=eLTEV$fTDw_VNK5QzU%QTk zag$u7#FD`@K0ca`QLJ&?YUHz?MY0?L{_*~m$5x!GRca;1N-@;)eK$zI)+aGpTFG+f zf7P89L^;4~oeRRYUMpF@ccE&<<&4Hb z7Lws45op(XMW~SgC>H~1>s|i@j_e$2S+dMX>-UvM zKETu(TgBmfL4Bx7%OK$u$H1&IzsA=lm_5YoRPlj5QS30@3 zi^*GixSA;b5s(vZV1Taga9y zno0K!jh?*Wc@@g*8Z?mHe`?xXN^RH$lF+vix2pS8mRii#{$I>SMnV4Ytu8AY_hN6A zmykLE&*@LvOhA$K&w6d0(p-Xf0RI5pJXF8&?hkb&@Oi~iCwt%(3E_Vb9>sHxzrbrI zDKZX58vtYq*7$x)cwfXA+`Jra{{V2-R7thS`@_^4?)wolTe5XhH5}FsS0ZHb~S}L)OLcoZJz=ofsjYz&m;1$lfP;0 zCjQ^!9+%=hKFV9$DKyJyZzPHjF(X*+%MHgIWkCYIvCuTDoomE4@LT|vk)umAdC6c1 z0dw0V{y^6s`(|sFUJ>{Y<9pWG116e~Lywm-$s;Ubaoiu9*aKSOo&W<%yE%ZHB_~ z%@AX^7#nk+%o?@g3vcZ24H!sOdDT;PI_<$H>CJrvZDfuqYTG=gR0ZwURRl17nfD+4 zY*%~mQp@dn)ToGeWF5V6^sW{VE^QhUoy^{1A6!?hd<3&-wdjdnTLV75#bJw=Eg3Vb z0Um5bPo(r6BhS*p?CJ@@99DL@rpc!PHM_i1Aj-UF1b#K&=(=%%92F&7o}3OUj=yQ< zL~({-bAoI0rCaxh>8_W!c*eEy4_~*8p=FuA=yu4+_r-b7io8{=Y8H=gHOaTOf4>E| z*dP7l)xSJfv+I5sS)HUfz!^2-{yB{j>7j@YIK_P~5>({ZDn54^8i_Y49!0LH$pBY7 z06Pi)EnXzpMmKI}pML-VNoQF0%|T96z^<~Grv zem_iBr-!2!_dAX%y@3R5%sUNG#}ar;zx!OFxu;DHp&3rfr$imPu0bOPzGE@wr!?cC^;v8oUX`jVpH=)d{ipOF8@lPb z$}fktXT)mdw_C{G%y~oX+zq%A;lk5d~#=r6Q*&=xKEh+99K_=@`COF5@ z2PFCeMIgP7`%=-Ywfiab{X*StttMPa6AXqK1b(8ti{ky4!|gITA=Gt<^sD()1%llS z(z|vBG5v6TE1U5jjC@6R1h+blw<(chF3{RBh8Vc}s*Cw#XlxOkmYYEN`ayvG8#;H7dcCN!s)Mc91 z5@eQHVe;HD7~o|5*ueGXy?^#e@V2cl$5zy@>?O6gv9)**zd+8*mHOa*6~pKr2#K|y z4hzLBx7yvHomhVZTp%F+75YWtABNVNZm)ZD3`mV{eRUk6NAZc@C-KNN;bt`bl`eR# z^gl$ehIxJ}IBJsnJl~C%`JFZGh-*=~dV1HE{8aFcm#Jy(ES4~}$Qbi>0>kmIUDjq0 zMnM=*IQrKI;&)4%22uw(uL_&xmV`^+jn9rX*rw60-4_8t;B6Jp-fGiIb0n66mC zzlk_uETX*S1LlbO<=x_bFSr6jE<(Gp5>j+ zd!F^EJX>YqT^?Jx$R!kzzNWg=Pd;8Au5#Zu-CwBmtX~oMl6`+r)HO?%&CTS6{)#wIJ+WOU!~XyP+u!L;s9nbH^Og}1 zSW`F|JpS-Al+ShB9|e9qirDlMS2H@{{U#88TfFjF0U=@1O8ZE;&sRT3z7I5 zqHcYkG7KCq68G-o#Edfqo$8~ zWSs`)f@q9#0qcX*eGO6(w&y3>zVQ8)5Bymj2mSk>{T}u3l;8vPJ*)2T*=HZ{q;wo| zH{AaK==Y^pVWZY)qKf7yE60Cpj}w2wAMg*vny=Z-(?D&)LJl`GPa2G$Oq%v8`M>@O z89Y|svVV)@m=hS9z#KV4&EzA79S^+#es6e><2Q`;_@{zRVCgpUF4G055dIna-rZ}< zZMAu3nq;^G&xweT=Op?X*3$1S^(`)23AGQmFW!vY3|vR-Te$bGCsDVPOx0#gmPQ|c zKYJ7b(M@#HZgn69=bp9C-|I~r_$2=TDv9sRQH(YT?V8Wj)6c|%JE#L@*E0bsF6TUj z#dVrAGD!jZR7lEr`T57aao!i!gcB;iG4yoy_53Tow{WqD*X2&Cf4o1>^q>t*A5OOs zIxHmZJCL~~ZpWu;)R`Lg1`gm5zr(@Dtz=tW2mrxW0DQn6wQu`K2ON@d%N4*M{<>g4 zO^!`A zxDsmDqhv@%eyvUJ25-fG59yvB(X1o3bUL%P(;R%3QaR7kzO(&_KWTfV@T&L+#aGPt z_Ezuxk9j%!@hap%$GJ>=r1f4uhQ1}x^vlg&`L8csrMQ0N=V)s0RB=`4_T*bN( zZTs&v4hrq(Aoew#^$T33`$11F&EK0lnXYcOjr<2d-YsCD$**LnPGyxre%+PT_2DnQWEwU&qXb7yBj+38nr;u5Erj4_P#;<@sq zoDK(bR;_gxvtqd}gkZ0w0D9-buiB%=-wD<$IBx#{wsbW->3WMZq7V9H{{VVFpyS%U zx%gxIPIx=w%ExaN(a|;59O;+tp`8B!(GB?=M1{{Tmf^I6{y{4h1}_Yo| z+5=UxOnH(^ZyNh%-ZD--hc(^kw@~R?d=~LwDkxAhUd~yUyiA=*Ejk~Z@rMx0EvFnF z9#)){+gqjO=KlZ%>UCBYkXT0?ajL2y;3&WpnwF!9B2aOKC-eUR^;RvuvF1F4oPYoo zPf*oI+U?goNX|3t6n~9<)f^urtkL*nv5Cdaz2E9oOHOR><~>Oa}{_E(#> zh-U%M`zM3_KPvS5xr1Bp2Ox~`UNt4+%NLaD4)5n(XM=o2E#wbjBZhl*7|&9j0sJ~w z=KNEa$};-YR+~T3{-1ICZ-*J=Dn?mtN2~Xv_iDcjubG?U63+NgNj-;p`S;@Ah9@@f zKEiX5i z$DR@0v(B^+4oM;0%kqwx9qX*U@WfK+cWXRg#v?i1(><%a(!3^76KrE@_adP2eUY-X ziqxrAoyLFN9R8$!mA)UF6@=!Kr|`$)M~XZHVl3p4-susts#{($WsLgA zCsg_zueE#khW;vPel)m9;+^d8*#S1!ue7l5vARDv>CdpQ0@Ab(wAkHSxC+d?5$lS# zYoQ{->{kFnBr1n*%%=^w<~N3ZyiASt=PAan#|`yP3(1kk*1u4oednWQ?sl5H_N^C}@7GJ5mtU2I-0 zwbvVRUViZo9vLIr>(4?D+D$*H3}g&|Q2S_^($Q@`nf2R%mL44@W@)Wk*gH>APri*g*IL9~w zuy3zfVwo6%@xDPF4JO8s(ZzB0omyB1{kujoKU&-JKmY-ND=$E^BYoqXw5p+a#sD1t zwX;omlE}P~oc9#Rj49{1s}&W(hE7{Czi(6D%d09*(ssFz;yWMh%MHg97Y7G8>0U9cTpcP|lsiO-aCqSMub}jO5?Qq3 zBtpstLKA`y<;UY*HSupmcv?n=CIbKwj28a@CcF$IN_>p^Sv#!{CD(jibp*sj{%eNd zCkCk8_;+2`t>eGcOGj&+%O6bp``1zMr{SUTAB=#yF3>6Y6!ah-a%?_YKJf5K2%YO)B!1fM&jJpmo-k1?+q+LGNIzX=?|>f^)u zP1>Tcg?`N|DaccjLH=X#tClmRv_wXH*%G^Pz#bg8@*uvr*H|C9ra)xL z&r>7qU&}QHmHS)|5I)@-!Mdb#jv8yLh|)J0z|PQ5rvvk?mKwFWxpXI)9;*hcC8f!V zRA}7}3bzCwab0z^hf#?cPdMs2*N1p>T-Lm4G}ro^h&2fuDM&`tP&fb&Vcxx8!1{rl zlr4|}!S(A?DDt}lJ$Jw{n7lLM0$8?3@=C~Q1OVU`Cm6@AZulgR_(pZoxWEVh06{g& z+Fr#rt1^}aZScSFBgy?SSBR{rQH;9mjWDzwdaf&Ft2MO!ILjb;#`YZ-vi|_}>!C|{ zp-ts^6`5^)5ysXXD$T|45Ou)ETJhA=yrk~WVo++)in2DmCn_<%nS!W7sk^5GB>w<9 z{PF()f{grRpT>SExcGaeT$i%2@@2hM7z=X42@`siSvMT?E(h?}*&h==FKOQeehhe* z#rK}0GEIp*f&fLNj*RwF*atMY#Od;L;n)itT)z1B4e+f&pfla`U&bgj7d=%XFK z3i?bR@E~}VmFv#^4?6J;$+_`?wO!%XLu{o7%sJWtA58O6d{flCtzug^{$#a@P!o9XW0X z=EVL2y~wRn>~KrrZ@H0Yr@QMW-T~$^ZCJ6-p$GM^sJ;>WE!Fh-?6m`GQY(y*tiO8) zx8agLhP+SU&74vA+TLr3#IZp-GmAGmq0PZDF&9E2#d@HZU{%M!20@O_JkLmfjTSb^*t|dRL7s zzu_>|t&+tgfguBsagsXo=~iIy1h!W&-W2)387IHJdrdOworIUPlKUZtb0h1{i(44wh6OACyh zJEhd)tA~wbxw;=Sc#Gk4LlZvFko>tltHRz8_L`|s01^cshDY_Uus$MQxw4fa8$zpY zZrR6gdigI+wl@(>oc{7w9CYhnb(U70ST{4_vwAS6B%r&PUu5zOsg8EHC)r8q zY#%p~v;)(g2>$>YcCl(8B{*?C)|lbJ|l z0t<58WpqoN`6crc`TcKOj)27!!Xfh?LH_Z+s6R$}IN_p{k}WXJ`6R~N>gG38R$k6K z&;Jg=IL$oDd$}7%hutgxvjruDId9c*XLS+70K24wlEbS_{1az?>IZy<4(%e&!5tg_ zpomVMX(mqpVAt*)1~+qQEIqTUuKEMf2LHtyaOt8I%@8VCoASY_&IjX?sU< z1!sf=jtIic!Izylj~5R6U9m|Y)?Ws^Z~oLd*G%e{8w>nvGa2Es60keuCkz_I_nWx? zoP>ZleTN8goRxKL=kQ{WKDlPtK6%kD{e{`;AEpp8o)gjT8@dS#$>ZNb#8GCi=8A0U zG9LK&N!Qsij4;n^Q;_$Gn**^XQVMsh;yH7^xl(%Bz zkH4L7GUCi23sm=&5Pf#^!hBWn(v)^5eP=&?>_J$uXNL^o_ zqh2uddBM@+Mq{IF@2CfxzJ6wH#ZpWSl16(X_6JyX;2oo6Ty5XD2m>D*zU>!&toV#c`)!%rsF%d&uTdD9MuFt9&M-;4# z`#p$=;galNoglzrZvuX)oivfnlk4`=j26*J0krZ_*efyng9^}R>ki;4XxaYZ)*3#4 z34At^^TKOS<-GNdzGaK^J!dUR+Juam_m+i~k`>{k1?Eym(B80Wv6%+d>am$9f+W5v zOJ7uUkaJsWH)(GsL(nl`4#BG4+S2;{{i{#O8dNZ@>|Spzm$aF1+8j?cA6shks&R}_gkUs z&(IB)(BYbG2G#+1*s5{4Z$A_+P-QZ8?pU~+R$OHAvsgW=P?=ryBh zS|a<<@+m=ukNX}37K4lXa}o8?&s}?;LOn|~eE&Nf@utnH*BbE<%CZ$k@Uta)J2rh< zz+CIJ4_R;^xSyL2m}(i(b^ks1sexwLW<{Zj(;!+PjHdN#6>nV%XO8!dZUyC&bpDlq zKIUt5T21tX$zMSZ>211jfAC4c&#}O5?)RGDBQCCSKS<^GQ%v+7p$Xw*a=S(_Fifr2 zj=5$04}^2TrFQgn-RV)VpGGSZHes8n6&seBL%*aD1jX#jgV>I?Y%|8b-y zRx$fEeF~HkZYXy`WWoL}9BDqwGdN8@&&~6}wOyzr!vC*{k!c(8|94(4>HI(2TyLiZ zu=%Dw2U~SfryuUy0lS+qVIbI?4~T?Q0(Kb!|80}FMB%=~hroznFvZu0zuU>+bqTD% znVh%>`Z;@Z62+|CLhm+H@6uqpaCc zapkFF)KD{aVtLF31I1~}jHzbFqS`k|k5apYKF{2%@+T6(-F)Z<*A*i3 z0b!ESt+F+T+3e;~~b%US16M*H_4+y5Tgq2n3SdWDJC@yGGD zV@}Y_rh$=$?eCjj8`v%g?L+Zkq!VUP^%Q#3;n)0-c)uVka2hG*^jAVU%hn6U-HL-Q z+=J+1AEKj;Qmq3StG|}*E^@yvg_=QhiU8d#(I<}#$y=s!Yx?u~(Ak+RK-ksTG)zs5 zYPSjSr2D+5u6{?EIR2{$+cmaF$m1h4a5g^A&*G+>%PVAv<)&CM!Hb;=$Yye&Yxh2~ zYhEdA9`}2e=<&gI+x299TbejYw`=XXG>akKB#=Vgnls9qUc%z81~T$o z6F4+$d!UOjU#i;_#Y#k$Rz)(vIS|*DFRd4T1q~%amtdPB|3GCi%Rm<=pSTr}j0vTA zPi?kr3A`5N?3+(pP77GCFd9xJwCX zhH8SuyrSH1rkvPpmu*h;v^4`Ta*oy(nJ&TJ0cf0_cw04T_Fi5O^^&c9{o;KAf5*jc zDj(LLD=rN}T_{%w_?10oZBn10j*}C06-ly0`zKp5X+m$m9qLs&2dp~nvoLVHjw0$_ zSk=ybcW!|4DiW({clmiB<}|A2S6Y=U$}AMSO{ZuKbh*PAx5q;e8qM?{E6iwf0*jRd z(z!>jyQ}fHc*-vWtl)8OwtU8>N=ZjvAh7awmDby|aTGVzoI2r^%bDuUa^{Uuj@uyT zL=eNeP`_At9Z)exH*8RyNbFS?Xw8Kh^ll({07IGEhRRT=_WUQw2AW9v%^c{l!E^=o zPoXlM3LKvKM-7$Cj0rh2X$z6cM-_7jk*cR6|KQ&gMus5@MB*s4H`n$n^SgK2!hbhp zcOJItT-MkbQ`OSs8Th2aZ0{Fxf6SCb6>(@UR?yGCkFLtt`WYR80M?6c@nH$g+bNcs zUp|ZPF~pwx>FISoo&5gZrI#z;a@pnX2@8k5uWXs~2*f%sHvAAa4SN z#-K2&*guwWXswDftQwencq_=h#g5`vf@SX9vxe=2oJ{Z?EN*vrv)hpNv~-(zR*8>3 zamM|avece2@DD^I2q8LJ$kJWWSGEulkSF_obB*OOq){X$;@2E8$F|njzg_w%)zr6i zUC!e>vY~9ruJv-@ORwzqo~8)Su}OSFgl7_sD1KYq=i-G1CqPctf2S!i~z0URmlT%1l_F^X%q}jZaHqD);fvT}zQz?!FSga*f)Bi^=0_ zQ-Kfg;&0sJMea2p3c}UR-Y@C{tMm17zl5RB<%)rcN%0~N43ouoe7N^}8PsLph~3J2 ztBcgRxh35v-`R9xl|Dx7nR(3H_tt`ZApDmbKy~!6Qo^0^l(g)fFZlR9qMB(7Z|`r^ zr?QIo`p#|QCP7hEEGNjNa&hnSJg#>1$mD*r){{%+L^Ij>gqSHcC&8$VIK-GcnDlHE zX?eiDg33nu=Dtzks2IR!9+8dT#1#o27vO8{__hTeVmM5j*(Usx{SN zri@+wXddM}CjKaO7-E8B{9{$|PJUiX+^SQui=(@vD+X(s&$6F_u?B)QV+EOHpE6eW4B-L;!08_5_}F#N_vcQ&=U;LMjY?5urr6x(FtkO z6}UD^!pVhkH{FNkZ@DKXnH&toT1V*5^cji!V#X8J*v{ip%D$we>rkxlN;hfttQ5ffWy@lWHH)L`LX8y!~_idGaST*WzC zdhpQ0$Lm7ZMH!J!Ul)8|g_A9xJJC`%-e?Z<=~$5wXI@jgnG)yy1KILMP-pax`d4J` z@d~YAP^Ban;BYMaCtU^+nyqi*VmBU_c}DRTC535V=daeW#@*r^VcP{Jhy?#_*)H;B z7yw6TKuU*Thg=BLC$(E5KVVsrrQ6L%oXH>E0+zE_$9|q0Mc_KhtZ^exW1M7^YA6y{MJ?>iZEl8B8o0w4o( zJJh)?buH0KUsFN9#cA&uKK8&U9*f%DSffxDf~$O)F$HWQLZU0p= zTp=pGqNMC>rn-i2*GMvRTcNwosM#=Ml;*v_eqLaOM^6`_CovVWP64Rdi8K8JMWU(Y z#5LWGE$;t}E$7=C{7%4u`~x9vj2(+hF~H+b@iB4W<3U zf2>AA#(eH@te6RsAz{2_fc&{DBJ8gB@xOYWLo{|1{3f=0ZNUtq+CmS~8iC)>&zX~sb8HVy2kV3~LfXj>$^X9g6wi6QT-{-9 z8M-99yG9rfo^BIUnW-kWF1@+fqT2pat@zQ?rb43H;mCjeRMct{*o(tmGe6_|zMOgt z#S+k97jehk2+58mIi2pL%aDDS)z%-n%Nw`V!A~dUKm6(QXB*Y1spwbk;zVSYe;T%TBN-pLe8qo5OaN?$8^RayC+%S+CeW|xXy zuuE2WHMF~>wlR_=`FY)ot7`4RCMmtN&D?ht=B6XQd^ovD)j+pu=m)g7wS#0{$cDCn zks-n%w+hSOrEf9RN2T9T)Y1@f@GJ+yZ1xsN0VtUF3^}8uY4N=m#<_rLAa&iHQ-)lf zx3GXj)S+Q6h#m~8)1DRalSzuKy2z1e+ZVs5Xlj>DXF zz~gz_V)_gGr!Njd=!*@_dV_`8?232BSs8M8)ggRw^Z5y5)JV#ds{rbFk9{upBv4ZM zdBfDjKhSB%_F;h178u9pDPGh}rIDKQnFRc@JwlLm;aOE8lAw8b2Zd7@f*a=NBJoR3h?{my%-YhI^{n5+KE`BKm4 z?4{!G*h?o%fuZV^K*fQeqVSRtT$w9{{U6aD>h7k-?8gEn5doNPUgo27Lca7Y>Iq4K z`y#jFOBWCLmPzG&G{O2-=*dB_))1U*F+hFZVlLp5hm+Gk5WSdgXFnEk=c=6T;k}{1 zU0&dz+HgBjrMreykD6com42WGe{uEjK_}KhmB*H^Q)9Bcz{LBwOY=f=%qmE|gyc(g zlOK~j48?1Eon((0+?~saH(%ve28B~7ABKJc+Ufl(csXumVMimD{FHV0gzl$iYwvyU zLv#E*mAuwS2L`v)pmV}Mt=aQZG);{yf#oGc%E@B7*~od3nkLMJPEPxIGUNEl0vdPY z2HWG0g?u}-DJd~`B{a;7aVte-`$0_K<)6iQti%8+C1nYe*^$*dNQ5EWuPJ)}G8*qU zR2|H5`KYaNx$V?PBoM;M;XK`P@R+hs9MkI%DEuW!5gV8Lni7UJ{Z%W=nxDftXuT?+793n!|KWbbubv|&Hr?F&sY}awMfoF60I>f9^9)=qxJVl;B^^G!rz{Kc&Ur!Q;{93;egI_S9!Zu zvhJC7IX-3(VmQtpW!^z^@enU1vWS_fVv#IP^%pZCXUXMy7jXTADaZTw@5rJ|mUW(p1~z3pbDL&O~QE`3zGwhc92&6d#KCXNH3IB>I+SDgM<#eZHq^ZlMV z(~?B=-0NpH{x{)EATz#JlGlJUxc zs?_+fQ|3KT$XjD5DNGJnnPJ;IK&+rRNYMB!eMbA?hntE>9KD zM}htjetD?^rgDV>wbJzHEO`#M;IJe!$J!%zDB{}zoP8g}62Thf z(x4`VpZX=g)wS=>Gv5OuSBKw@KOM4LXfIO^%|eUIe$`DfOK=bLC%C(%e8;&c^Lp1k z6R$j8Irk5=(H2x>ypw#X)sd|4ODWc0d1A1sP*%EK*N35inYGj!>952{Nhla8Rp7=j zU2ZX0`FDqtVY`3Hb*~?aj5rN1 z$;e}|5P)i%D*~*j`I+~V^CaK6%&bUO>Rza$%4(L*hDuDK9D#rM6%bZA`fKL3WfR?x zI9(GS6OT>Fom7axY`Zere79QzKkA3b8x_x#4TZ=|WA}^}#($vY{xp8?7%L-j`aZdr zdatp4!KX?a=Fb8Yk*w7R^g;-NJaYK%=rT>bmayCxW%Yzmo}!@7x@HP~*D-L&@;4Rq z7!Y1pmJUpdD*u;H9H)Q7^7!L-8UwwHBKQhn3v`q0SRTUwjl(~j6Bs64*Bm9VHUStA zh%7{fgD{K7{rqZt?2|mVb6pEbPL0QJ;LmNZYQYIh*>P6_i~oDsl=)xr8xM~Ql*?>1 z_-btia0e`8#cI6`2|QLFe4~lW`X=_t%DWTH2XS%8h~w;qKVB6WIVK9(fST9!0&_mS zM{~rFjr9PDPv{$2U2DY9AMyFLqICC4rNirz-%qa-PhLHMm*iON5ZPKu#t+j=u8{LN zJA?g?_pf)ePzY9f8==!y*ML9ERL?Al1x&APd-Hu@udA^?zN4z*I4E%yS*P z%c^Vfya!AvL09bq*_J%3gB{-I=#z^%rYt3S@bB9{ufgy*k@LB!DcL|3K026h&=v3w zor8pZsQalVwm(`X!a4SGv*!jDH&VS#ox+30Th6~c{(&SQS6ccc zJE*y#$BO789)k|@NUjTsr_5^=YQon+Ff{Ekcr#Cm>?ad%)PkEVjeCD>Px!tF1FO1& z{LluZ51%Uy8S1)|lRW(%&@l9gYUqhY$|U|%Cssa*d~Ug2kS$@q!jPt-8yWlX5A^4% z1H1|83zSsUpi{gaj89A8*2+vl?PcC*`& z4Q$lrP%zBM>-{_|C5Ol0$@PG*=Ua1w>@qF(rrG;ADY{Q=gW=?}e-mzN!w~yGZ zCIgHXB_gA*B);Qa4`{YMrUenN;zc7f{o;A`NsSTXu3+zDwT{U({LD#qwqUxx8lh-6 zM+ET?0Q+1mI{2E?E2OpyY3>8xs#Xn4+hiv z=dim3AXCpWF;q-Eg<)Xq<2TWz3#09SAUPeep%VqTg8nqm$s1%{8Plq2onS0?^@hA# z;;Ln`K{O@~h#JP_|BVW4G`4S0Tv_yUhBg+f=#)+fa`Ac!_>&AFMlyODu~~&h?+Mx) zI|jw&)aoCj(71-uQ;D%l*>CooZ5p;&!Iz_J<&~;0)4@DqbB41uj4wj9>f-c0l&qWI zEZ;b2tra{Fpa^D}@mUAywD>9cY|W7)jHNm5vAw<2Bu* zU7gX7ge}8af}J=I74<&JG1R9`t@23o2Fk-sY<7fxxV4$kvQz#|s{TZ+LWea5KMmMl zvb3)8i$}u`qI~KqY^wu3ghm9@_^I>q-q2GSHTpO3(K62J<D+@oZ z0V2$#W)MHW&tAMZcH&nlPI$HGLRDw644MoW$LjTX`hE-Fo%rJ(@a}L8`Pww(>Fn#0 zVM()b!t92UlLohKf#$u!ade)?u5V}lP@;A1+8s8PUSXn1#Z8+x!~W~^PR)ppJv*GF zf2+$>*GKZk%Q}2W^d;NSFZx^hijA#X2i_Q`GcM<(|NIrK+1_K|jthj~QQpF^;E^ZU z@a$e`?yi3Phtlt438K4U#6bKudr)m*?@yB3 zKTyKlmriPwNQhoG`i1_|1_2c_@G*uQqMK`y4V9=~Mg9@UnPIA1sUjhGM=CS1t56eZ zv6tb|FdsyL5}EhRCR8@39-*plBv1N~ELZm=mVDPQ*+G7$*PNJ}HfdXWV>^^3uxmqT z555!;SCLL70W;Bg+E0c15Sgdp==F0d^niByED(Exm>B7x(tt2sOM~Sq)5(7nS}976 z4N$0m5-hSLFzyi6h!ol|RS_pKYNl%}Dal zN#yE*9)?+wkH?6v5CecArQJvzEMl17)qEs$f_3(81hSFAfVYu;WGBVq6P~xHo4FVd zbF_ez9}awhpfCu*U+5=n{fY28MWv z4o;$kw|+M$`(N>7L0_#>g7vQoeU#$zCrmuIk4U;L@r@Iwt1SzMfOPW4?1876Rum7(Q~yTYUha%)&)Y^e_34Gp2i4W|RJ;c`P7 zea?>}B+M-a9Z=*gXH%dszmXnln@JaoY3!bQi>bN&+|!GE#*03d8Xqu^iPQYcj;d)nU1AG zNE;Sn_90{0Ch?=8iK~A4!v8>UrLIupXAChxEC5-<0gM(fS2pV-tBhj4i(*V#$ElL@ zrO0F$O#}Pzoa`m|deh9_b*`iFoZ#vsW?-Zdn$bexRo+Y@D%AMa9Imbr>a9nv=Y#+o zV-WmUk*qd&{sf?um@UFSwbsQm;(Q+5-Vb-(Al8e0~mu0PHO zQ_6z&RjD)g=NNOoo$vV;bcGM-poY|+RGfnL6|)I{ZXl6M`eE&op0-xS$RGCa7*AtZ zzjE!cpMXxY#!|Kz`iLXf!~plXl<3T zYtv4T_g5rDjygwn1T;LT8mBzSAU7^Nf{4+w3CUp=RWIMCWVdIYfhju4g2sWszUw=o zP{bQzqLn{r$Eiba%{vWNwM|o^X^(L};vzRMaBUM%X}Bb^ZcEO5_ehZ}n?TFLaOxXh z_ino$VLL4vVr#1F)~warQm(=Px&!v^@P0*)@q>R{)R@ka22dP&n`IvTsrgJ1*^ zbkgqDYBk>2L!j^|0Q9l-lZ=;z#d7q*$W{4N+)lOsXhk1pb)A&JSq*CZ4W)R@nD|d$ zvo=nkV=E_cg9e~aP)s+(b_mGF%v0XZRT>qcCNBABIdYQ=99+X6SG>zeF$#8vMGJR5 zDu|7$$%CfjDkmU7L1qOH=arfcdM$hbVw@l%MvEHWC-y)?TVvk>PeKI=hD0N_$e4j( z4j8Q>i`(B|@mnD-z5Wt)KCqZVD>4$u-u{GU*zwz8c-l#2tVqop=RKeRmq`BuHaIdw z6Qcy1Wup-hHyGl*H{}Yzx5H+vrFdrmF*0<*#R?y?v@?D2*p<~GRm0ndiieV*ht}}| zK60v*1-LJ;jz|dJ{GeYys>lJl`yqh=xUGpe+w{MloV~8!{|926+bqcpsUSDMb>P2L z^NDidZoItw`8xQf%u`1lZ((4IK}b2ii$4wuSAzu$wAKaK%q!AvkJSyKqpL%}f0;LQ zjNaRgAY62Gtdh5kP1o-^TKW+}>3JW#wbh(L;}>vsHMW;p@i~X9_1QTTs|G(taHPp` zC-}_51(3FNQXRGPk#Gs#o^+(q{lPieAzA2`?OgX#A4mv3JAAPQ4$3QDG)l!YRPe0&B_*6OxWaUKrU{_M+tngYYa#vO0Lq zf6fl_3HnW)_T3bGqXb3r zte)l@8vl8t&&8ilM41Fc?b@3fT9s|w!Y0iZv4sOL;1_w*rjWxAsb6b&TTW&_%3(Z% zpD!y(Oe`++R~)}CL8lIxZJV(_SiSiNTDBekh=&kRR2(Ur-*QUtAS9{0GNusMiiSq5o@qlAzZ(unR+?#>6+OyP3 zg4t~$e7n=+N!hFjAn{PQYP8UBQ9d-UitcH_Rt6&CS5w~W&i480875|?3K^HH zR}|bD3Khqho5$$|^0J4R4+8!4vpI4mJZ9s0bi6Z!J&ZuDVWcel4C%h0tf#;bM9dQg z_$vebJn9FDty{IMeU)}CDjx1)Hl=HQlNWdM=Mn9ng*a8;_J@7S%!mM=K3R||n6Kx- za&SJ~jfkI^p!d;UPTY}`O;IgT6S6!H22x|8BtBwW;$UiKpHM}sdV9SCsRiP;Z{OHZ zn1K#Q48#s%=5d1lPWlQRv6?eyFMsR@pXpuG_tWD_BwQo(8VY=CDr-nsv zKRqTy?Y^Go2Xq`Y41|0OKXNF2co4j>T{GI)qdNF(z8DB#@wCpT+5A zLq%Dp`r#{8CE>GJJZCYhEbJPYytOn>ZOjJYjXQgR1fOws6E2(8yGVS}kp29t;w7Zd zsw%zGvzBpp4WTImy9!Z#+$SG%Kr-NXCk0#l57wZQi^XWp#O{ZAzu_rE+E$++0~h9| zSfYX8OAY51v~Ghhfstpv9`m;hy5IK@sNdds5aaUULUmHe^2b8k)8=0ws{=xh+dQ%6 zxihZ)BpoKj^1}qmucD|+q;Anmqp;mtaqGFfi-Z4qnRV|Pt+0qP?>Ep57RNP4L)nRI z;>4})vI*@E3$HdO=mvyy=zy7Oe=35B$?vtai9y1150BnTPRf*07Qy*mW--K&S-qSl zBhnf5F&ciKh(#-{4_{1z%YK18rZhZ05|hX{x0QIuds{s(WAyjP>Y1wk`k=B+dqJM$ zoXlvRulFkTk#C3+owg4qZ8w@XWA_)?z2N3v_l?hqNOk1$^S}4gENfIhxiL;8HDFPn z`qRXA@}De9(At}MJt2*)v3{QMb9nH`wu|IgKvyA3$1}vHQwy%%gJ}^L@P{%HIGWPa zryZ~32k48o7^wYG*A|cd?qV}!T6piLol5Kdy5PO>)Y{0J(#tn~XIm`~rbgK9B%}pM zc_N3Fg)^pw(em!?*%rFa+~cw9RSXqKy}CxaZjfmKjfNw`{7!Km#&u0U-sU8xs7cm{4a zY(C)Yem%_opFsy76FMCJYx`D+)YvdB5O>_1c)T~-)6=TWcb49U!#o`m1m#|a2y*;+ zf&+T+Dxayzgo<+b9?s6S4QLJ7muXKIJ|lfHG&V!IO(tzqmH&eXBZOGI)$f_g7unHE zcOsdpPZ;Ho0}@UXMekYOfBEZM=>hS}9+T%8fgeXT&^~R1Btl;cR|Mn-G17Q}gsQ`fe=J2*1Y)P9N}r{B zEpY3yXT42a!{|a%6zDNV#iZ*2#E`l zKw9-ZJ;|PEx^s$3o*^>0WzF$8%t8ce-|U8rU!M-fbN?D~V_Bwzz7IYM^oJ_nLHh_6 zlA@WCIZJhj0sbC_&TZT`prKRie^uqA(HHOSa1+JzAA&w?J-{^GI9p!Ak+;c}YJ*;8 zTr6fZx1_AAPR*1-2WfRPGkHzSd1@3#elkRmA*?04_SetfKeIlNg!qQccx!72pICogB1 zROUjPDZ_;5qbmW2o5^tv1k+*!HJC9?=DQXWpWW+J2vn1GGhQZ1lcaL*kx?!VkIB`% zchaSaz_s*;Cga!kY5QS#gQ#?XIIQWFpjMHR&t%)_cWRf3k zN%ITQ`rZ;>bQ` z=va_;YVXo#J7%vrub?}mZ(k(tdavZaIOAgv>cxg_`U06pz+D*>13;K zg?B|2!>^YKt4S~3VpjX{zx&;d=%KxVF(iHrlOGXwd)%YiM_uaKD0J28$q|O#eUnxM zvM^N}03NM8iu=LAr>Re0?=5n@SNJ|WG@o?+ko7ir2lep&r8ADST%hO%EINo13AN5Z zQ_pjIk}bDv#@BEuG=CMbVP1KLa)a9@dcyEO+*^EYnR!j4hac=lGNJS7_l4NkYqAq+ z!ua3Zu$XqC%8C5rn<71>s@H5iiL1kB#HwGf#@)0}X@i(LVzO=p!CFEuFICzKoq}JI zohBIyRPYb_SQdQgK3{7ex^aK}NwJmpqm?(>2w#I-Hrs;=pFTe{ksquuv8G;7x?NJI zX3Mx5j`eFiu;QoC>#y#DTPJ^5bh2cVJvl@2pUYHG=w(}B?aIcn$}Y^W^+&8CFq_C=T)b}dd(H;IzeB$v z=h&IBQ--_azO}g>1mf&UQv*=8t#1;Z`NB#mV-_MK|3G>}DOa#`K*k%@P1#=hR*_%%f12dPn za_UjyNs4=w$T-R{WC#@zV1{(VHZ@n{lgZ~7Q!%6m>=mAF4mo>hG(x~WFYAXwob@*SY;fuGS31v#d@4wmsc4?zO{nVrI6*DA zQ~ZZGH}ax(Wy|2lbfHdAX~GeTS1!+*Jt&gbr4JKsHLlSb*OJ;6895(wrw1bjGd7Js zYx8DugvO=hpvhK_4*k8UBL2{LI!j4Y%Yx}CuEEN1faaY=9$Bb9%w0U+peyp7U~ETN zATlW$1eKX+@U5-hn=lfw!LAvxgHkud2W|QL>yqHT93o++g$AvHjc(5)vrMlOBPZ8Q za*{l!bZ*=y|Gs$t#abs>fXOe!ZutP?1JO@v^!>d2_}Zf0Syw4cJ3@#G zyNAvr3k7eO^>o2PrvAyU;(70^5U)gv;jXZo_tyLqiU!$bhoDf<>?xSt&}@2cg)=E~ zjYD=IuP@beN%8lc8x0Y~>W>eIoeC1?Bn8%cL>Q=B6XXZp;pl zdy|(H79Z-#|3KT;R~KmP1N?s=HJ+}k|CEtg7ZU`Eux4Q0U4(1M;w0t)l8QoymO%3V zV$O=C^%KzZ!z@VREs&pYde{9&I)5@>-cvP(Y`BW4xqjn6(A1$c1JtWA(!tu3j#GVb zGF_9rYREQC!mCP+f6SW)XYDv^j*+Hh@su?L{OoVY@-M(gu4QZlQp7AWk0I#v_nRXq z|1MZd;5ktOxV8V(HHtq;na=tC5?66wWSmor@)wZ;fqHMd!reyO;PITCIjW<872Ayv`l7)`e3jr)3@;4tgb z33^lG#N;L|y&!}WV^ZcOSI+=V#&#da(pl0Dp7;A?Mqm=09Z653MEu56+ zLd%(s4UZ)C+_KWLV$9jTZp+XeA_e} z(P2^(PC{Y9f3m&89Fq^gp;86;VCA#0*|e$s@$9(D@pKe!4M#}hSdaWMO$q>v2t5N! zaSrHlKU0*Y(&J%~=3jn07nB>6N%r@!PH_^~ndLHWv_F}M&hIJn!wR;GE8)lX2$fj8 z;Nj+at*LWx5Z6Ts!>Z_`Lova2jxwZfXfPHAhyo;55jP(1!Wu%NeOkmVCsuM5%J-qV zD`MZw3n*N`f;BFwKh+~;!5#+Dd}A`G+;uhki-IJ>CQxPJnkShW#bx6!te+~IzC1}sLOvDvGwb`-f+VkI%>zF*1{Gj79;}G zYM$QtvLwn395lp!9cCpj{T??KX6N$e7&^zm9X_5pG%g#VUHi@5WHks?ZJtS9I@?rc zzsT(o;jU3Ghm|Ze3GJY{XV)%Gvvf6QB72;hrDY~0Ktu{9>VSRud5H^q!I!x=aZd3+ zPIXwBMWxoq+u!RnOO~ zpZb10@tA3{UziH;@ci#s_+*UZPW4%ZE%(ZHwN&0*gBz)_ktwsPg-(i{;-H3w5?G7S zcf6=vva$+a8em>usIH`AhWuqNWxRsPllfkW9BZ_QvGLw-sh3jv?u4{mBZ>KB$Va8E1XXrUV;I z@W7oegsPpJr8)>9%H;=j^wVX)GK(f0=z5Z|hd;wC*=3Yb-ZEbA^-k3sjG2&Go?WSYctBSH!!qc{qS)FC}P zo~N)LGyQ=q%<+<9c;hlCR5)f*K0teS>;2qUsp&rruH~BA`cz>n-3BUO=XH!0;C1eU zBE2(J_zQb)6mv^&EI={cj$?Kki)4Z_0p}!-(z%u*F|tQ%!%A0d`Kn7OZ8WHE=28&I zAbAMDK;1WSf}{iV#&g)))jTggjjGzq30sRR%y}=n3c-dpk~(CDT=X^Vx>v)CeOc!4 z?c6S6)NL5XcCPDdggHze`4NNeMh{b5=fs}?T*u)nNhL;wqGyD>IoOV>7?IxutDIwi zSE&`OYbjXDR2*)3&6U6Q1n^5@_b^&9BPWv^j-+roQ}>h5oMaJ?T=3-ZUfaQ_<`mR? zjkg0C6Gzi`Ofnpd=jeDKjy6yQqTSs9EUyAbsG^MdGXNSZlpfrM!Q^iBt-lQ1&*97U zv-2aBnaH-o4T3;UV#(uc2FM44$l|nXnOw>~>#@Xm)52!qZm#sn40FP{y0F1y^7F%{ zPIeyIHsApE}3^ z4o_@T;+(XRs8Y(n^PYyjb^VV1DoODZ;lR`G*d13!Www!7zGsgZMkDaSKBB&gwk#N_ zJvadL6-!cWW?C0TPFQ3Cx1~30EAP-q~ip49Dl1dO5Q@Tk28_T z&V8|39}Y1767di?JaRh!00FGz+PDXh=ZXy8;umn+ik>>-oYI*5$0`O18Tp6hQmPP= zY&mYj)|L<7sxv7`JE=MP&>}R94y62}0ArJ6+$-D`2PS^&~7HZl(BIXYD7;f zaCzkZ1NAkRt@t`!Fl?1sQWW!UBqM;_5~I|Nh4(oftK3h3hP$e(mtkpc%OsBAk1z(@ z7wAqp_6OFmyldgvH3>zsvo)2e$})@#sj^Ey`>B!v?!=naRAw%Uvp#&1#!oqTE6)ks zeSPb>@V>2KW2)IL{3{)?+KoJ5nXk(px=u2w}0mI{0Phd+n4GsEKR z!&;O!?C#3(<^!Cp(UY7X^VECSYw&jVZDT^TSy9CH&IC>dcc~dep4<>UIbV8z#61ox zRiW+J41+;3>HaoTQzLjBrLbcNy#PM~*Hh)AY5t(&aE*!7rMa zBMeI9jCvdz=R800C8WHwzll=H`UzHKmLY<&1J~D{{{V-jYX;-0IqOC<(e8f7Y7vwVBKEH9Cl($xZ*Pw4IX$n9AdEk1$=B8k=#@6F=9t$flI316+dg7Y_ceV?=mC3<4%`p|A4=&Z2Lm0T(um${0R@J4E zT>y<%1szwp?TVYvF*7C@AUW)Jd;KZ0Z<+*#M)F&BH{=t=Fg1Q1U96rj(fr2!>&)0g z$@`68JA8S!-|@S}#~B9jbN>KrlD+=`z=7oWlcWoYLrWaZw_@Nh^4h#RFCo=Fo&I;FN+MrOxhwDhfgBTAP2Ma0A|!ZrrZ)IIU*_3zsPxoZg8{{UQN zVq&zlKRb?hJ~{*3jQ$*-O5X7gi_$&1b%4aG2ICp#GJfdi_>XM#89l4RsXlohRfofJ z$5KBR>YrqV>~!E-LJG*r`xu_fkq&-X@n z>w%2pDJY}5G`Zg_PnG^L_}}|iUXw@g^`ugwzS7aKRbG2_KcM_;)4m1#EY*B0Z8clV zJskAGHE1Fyho?>c@<+|SEz?#jNv)kt)x3%sLvYa^`%VGJ8NuXYzBu@^VyHjuxQP7r;I`60Egz^onR_2f__N~d@c4$- zZza+@kaN5*%E#{vkAA##Ij=&5)Y53qRNXY<&oq<8vT8PeVAR>~1Z$O)j7u5o!R&AW zt-l0#%J;&W<*uot+zD=Nlw_ZoWkP;rZ+vinO7pKh?VezR6BQ0!`N`ftPPz6br||9j zX?l{x9^{FIHoMNpi0=%4% zDTX4{(YlEQDZ>_g@(vgjBNLNoy6B zsIj+}!ItJQGIB5+ekwx`brsX)sBY!QR+nxhVq^V?rWz$k27 zMYM5`y5s%=bDzS!N^-g6RgI4_)->Rq-WuC%0)H{Lly}ZESf$jeQvsK^O)5Xv5 zNA{M|mf~M8OVwrm$-2qHl#qcN{X+ylooH%S0qm|U{H)7v8WwPV{4RGP$4sjRT>Fai zkBBz1YCay(^@z(Y%yIc z(zuV=x8gc{UHB{Ee-e3uOR4QvE3gmUxKENme-WR?y)mt~vGlJ)nDXp%vsi{>k@e!T zbsK$z{@#7pcIaOb+Yf5F^I=fgSv@{{W6HJ57LUx?SF${Q0q+ne4-n z{HoW)3vk{ny?&o_{{TQ*t)NICx<)6EMR;%clD~7gdFjis}ZUTI|nE@x;Pc#>?10m&q`-ZSVhJ%xFdCGQ_kgoUAV zM?=GtqaLIG0M%ZJ;r%Wb9%x0BHV#k*80>dr+w&FAX%RQHx)NNTC&u+8Jy%kG< zR2*jlu%@(**gM<2LNeRYzUme}xb^m}t2>xgSNE7exF0DS$rz{6Gyzza_yjqHja9pMt)E~^B$o~L3$ZLz6)L2cqhH@CQ05QSG1HO3Xx$mj#!s;i_ zJ|xjDZD7BhsN#EkHL0VCeOLi}d%YkvnM)P=c^ z%VJNM6p%nZpy!Ty_ZY8Iq;ApiHQ(M<)-GVVh=2l<(37}>>MIw+K4pf!hh{{?#=sA_ zF~{_(`Ze5FEIj53xL^gzHPTqy`I@D_+0<=Dzysf_A3=)elI76hPWqh_0*4%P-k9-* z9fe$F0Dw;KlGwWwzys7&2Hft(IQ6X(z#N>PV^GT`!;#R8aa5SB zeIIj`_-Ek!0#Df@>Hh#+#dE3)ZXt44rg;48rJMdqzl1Z>?2-2W0H#8)k`TU!)3y^c|-h_=~ zV~mFx9@S=O6c7N*4_>*Zq(rd;_3c0&ck!cDYhMVRIwE76RF!R+zquLaL-g7Y;a&kY zhPu7xi8|S&_T`l)_nIwvQ zuN%%oU=HWyAP-^371DTvR!DU#l}mvd&j^|h0LaMRN8mI0*Pj(_PgYv!kCpYW4KAPK zE9lxumg3GfF)YxLEM&+_9(cosE#Dj09+idSZ?S9h3v#<*)FNw$!x6X7QW5s!rtg)x z=m*xiKZ`f7Z}CG?W-+u8ZM3}vlPD~|x?m1+K2y*8E6690G5C^__+MVpWwyCT)8{0I zAO+oq2j2(g1Rrl&>`mX)BdO}%$`))5fM`=q%j$JiVW2SRJh^!;^` zJBw?OP0fK&K_@ao7+{PayrYl*09|?yiu_bA?!&t@j0lcFo_4nZhdl%AKG`C?KgBmv z+G`1^LfZ_4HWc<{1gZA_01EY~d&^VEuDM=^swa%?XSFLRS!}Lk9(0euk9zI%2;bV#DlP+a6oY<^T`9oY}cPoW=L;xwIVJ3GV@p_h-xU7<;R5)drO$Dg?XI8u zI`xBaQHToX-B>FRY}e{iD+twrARL_gSK}swZe!HcNWgC*8FDd${0;Tb8Twc1pX~AC znY>-_!$-Pj5=yWt%8uNEzatg=ROEZpOmbRW^;n?`8N(d$hR?N1P5@OT9#0%qBw@Fd zU@_G8BBw}NEshTSj@6-=X$m%Xlk)M?tt9MO&;|KNe)yzAo=76SYy96tMK(m@W+UTF~7%lhn#(gT%BdoHhz&k?%2NV({w$abzvqY~d zG1%n%$)31A^=j5OL}Rc4&>F20vSHMX-NrlB=%379SS~*!Kpq+UQp*kC(KOUM^jF3PKZ^%}UAM*06v?c7OYt-wXUx(I zSQi<>Mi&Dfs}_awbNsr*=?k;m7!CCBSyPd86bf99^G;4>Ha&>?S2aQ3qaE~o1-SRc&l?N zMUwpRIQ~P}nv2HjD|4wvNjXbnle5wlv~MiRA&yD2FQLN{!|Bj|6`8GgU^|=nkz)?H zw6~k&!sG8_t~%q7Om)p^HP)%6K8K{Gn+vOmn2Tpaxl0gBV?1E>Eyvcqhr{0kHEA?^ zj}U9I8LsZ|@I@dj%AJV^oSqNA9RRGSE?tcw8@+TsO}X#@W^3uBRP%{cGJK=UKunL% zA$aTFyt?zjm)i8=!%w%CN4=0rKpB51ebIsUaxhQSSJpbmfp0z`>#wK8tdPp<6wEo< z8lFHSj&YC9zJd5<@HnJZY}JX5Hf%Pmxi0vl+c zomUvfNen;n>hb9AO6nxWcJFL}4*=I`eX9$*pAkbIak4?Qo__ua_vv1C?U{FX2EBBT zpPRm?)t|B#?F8Qo{vuo3YIhEr4yM8zoN^#>_a(=0IRttf_OH{eO4+qLt83UXA|0}C z5)!PK=rQ%pen$S!9|?!Y2Jv2#Z6S}u7FGjMumhxWuW+@ z&7JIvSi?M#6Xopre7PKQt~vnYp2x7byJ%x2&8j`#<`?sJoF-2@23fs1s_h$F{GwE8 z2h2bO6O+=mZ;-a-Kv5qDYjh+JUs}a*!r>87Ntto;oNXhuYGPKD2&HET&x`_l4xMSH z1(xYR#4(Y$Z{u}KcMSU^Ach#nUjEd{738+g-R!N8Gj@KX6u`aUc*6Wg(Ob+`9&3%N zc?V;DV!T`9bXoYt;-ikYVE+K*G_Pj(cIe(d(MA_?$op8nayB+`@9b;Hem23o;^&G^ zahsvj{<)=RGg^C`eY|`Q4+o`bLc0(WI#o*;w&3*`>zdS!Rj|4Fx>iR(=-HeC6Xhov z^s7-qLFKrmvxK19M^5!}D1$aKFnQ@r1d=eZ@7PHLBOIT4t9^bfG|xG3WtjPKWkxc4 z{sSlQtCB+Vvqn?}Ba#~!70dXBNoTu))*?$t>lWg8RL*20-vEm9F;yIW)O{XVhgBat z=tZb%&!A{y%2Oru?gUYuLXtQw^cCExyoM$CvxbB$V!HB!5%td-?(Iionz_ zEg-zO)vhN|1)lir;bJko1G&q3D9HNftwG=~5RG?NxRlKAWfW_7aWgI!HDv`*1JejI z&nL{UF>HMt?G$>Ci9C59g#0%1OvPWy+=%C$pkqH)Jv{|-9|61({{RW6h%P)&tYT}K z*pyN-v8I0N`hPRtyjRD+5H3C>c-9R%&751!I6DE(5e@+S$MdhXJ`DIRw2cbcNZW-R zR~*}v)J}+6l?OMa&sNf{?eyDZ2^dfZ98rI(ENI#3`BcASFrtox`gW|HQpM&{2_xxU zGHx-lM~6-@sZ#Q1ihj^KW9$AKxt7omwZx>Sxb6@6?_Za{5iV!8mh#>`&~1FGl5#ow zy!vzaSL;`c^q_5}Q=qgGJWA;UBfqtxSNzZe?AHc-q@? z59WU=^{?5p$BCnOy6;VzUB76!Egnw?levDq2&~iPmCfqXRcWQwA8~=WugicyKaDZt z#zqG{>H2sN8W7vEG70O_pCn<1LFjr4={|BxmDr^;SUBnRtoflNo=7BC)T^IDM|!6` zK#b#>v`K?J7&!0VzPtUN7iYq49C|$e0Qx!W<+gi&h0EAt@d-fGCV6pL!?R%>Qz0{!%yX^Mr zj4_U`Naw#8t>5@3H;63ssC;**UbKcNXS9V@H7vxK*x(M`vVH5zKWP0;^-V)tV8P4C zBF1?nWLJ0l6!^mH;ZJ~kP9_#FB)Xa#nWUAoZ-^J>H#ho;bNIe6ZzN5UL^ge z;nr4LT^`p^*Y8v2n%>h(Q49*$3T2Vz!esOWZuS+#cst^*tKywY?Gb4fv8r4;CGH7` zGUIk#dIiV@wvZ1~#d3XKza`?dI=-=mbvY#6&(ej|(&8fMK?G+xuOIlk@lJ0EY1a}% z8M&1Q$qJ9Wef_J1@IUPhuUu-E-WP-6zPqn$dU7ecYYV$&w?N7n7|84f7!XDWBD@#k zuf@+2_>@aDUr9|f>gm&i9l;#rlSXxi$bdiB63+*c%_Qf)>2^+!x4P8X6+-86rh zyK~~N6Z}Zj$?+DmEv1V#=rH6*4RF3}T<~0ivH*SX8y>aS_!ZjgL${O5cQQh< zW3wwRPyWsNS3B_m8rIG$m_s$jn;?@Tua-!`9@J2uypuWc5qh3e;$;5J*9E}9WdWT= zcQj6L*!3a7KVPk2U-)@$^i6w8Q=hZkirL&mLa$J!}36i}46UFNwSXdmvd) z{7r0-@tk2M!2bZgTk|#duFMiWKU(~F_;urHz6pNPx)+EdE%snF@09gU~WL$sO zGH^XWuh^(ABDsb+ppj;VRSz7C$aNzsN3jGS#=GL~k1lG=jiC+Ksj4@&K!d!K(Y5-scKdn;mWv<^D=;zYy4nI2H)gZ%TpQTgqtUG*RrSa0~ zYVUL-bH?{-d}pXY!=ICB{{Vn3Wx&BD2N=am@hzGk8eT{NL25aKQ`LOP*u)X$#eANe_G^QVE|*EoL8Z}xAvEZFKtNN=)PioM>WBO z47~B}SXW;6H*;EVOBG_b!*mR!*2bR+WD6w6%f}0k=UGzW%P8XquWGuddVpQR^(r_9 zxSr=kNql2(1b!8}mM0OSt{PS!#83YKuDm)KV|{7hRuM-A8N9KKF&t;mV;|(#w0M?R zpTqZ-@tw$29A_EF^6&ZAf|AP3a_$-dHZoWOFnQ$r`ubO&U*b(4S(f|M+*#;4E~yNo zWKg82iyNf3QWeQ32eBLyLGCasxYMMbSJ^j_6h(u(LPiwrIZ@D_gCCC-=Ne{-b9bpu zc1eF}BA+S&a4q6SEK39YN9H@ZKgd^GqgtkwYHnb)I%G2f-cVB~AQO>{kWWtDz3Ii< zV_CsBr}h1M390y+)@Qqhdx+wKBC)WMfZWZy?&SIa5BOC6An_fPa5SlT=E4+^g}_(o zl5vg(0Iq9TOU+MJh8L3Z-qmG~b4?2%W$OO`d!~JP?~2ie3wdR~iW@ySRboiuXN4cG z?2>WDG5OWDX$omr;chOMQ~Ogz6}lH^K{6<21EFG1b5i)G&i?>UkL^!!95Awwnm2&PnU?o`bmcsYxBl>*RRX$8Q(gP5qx>x2Vf^HM%TNscq1#iWy50=nhEdkHVYa zF96v1-aSKAmMHwonfA!2fF-b;;L$%6^ie~)>21*37b!~xRIm7qLLE> zG6rsi*q%Bmt3MY$Du2Qm;EglG`VHKHEx@{(=Wc5!j&b?d+g=*hmr?jr;q5a+&n5Wn*8r1_K|C7Y_;M24 zP`E%b2}Mvs@yF-~JXZ}wxo&dByPbTa3AO>+~9y9*{T!ml= zwrx1b9qXYHiGCe;NF0y!Ncw-*Fh>=TVwt8Zs^9r%!gU)Jaf15lWKM_!!(gtD=9SP}750AfW zU207`;%9?c1M^wS7zc&i%;T@(qv>9Q@Fbi60EHG;3>guv)r+3H0LM}5yY;R^_UZ7v z(|CVF@f;}6E}e1Zd0=(i=tuHl_}1U-`Qt4@$Kh6;XJw;Fd2I-iHohB(Z{9HgamUJ3 zb?hs{#mD!TXV75f`>P{=#9G<0f(WiQ7qZk=)(e8T1+3wj|M3aGiYCtT}HsQxy?cUzt zG4wU)nzw-NExbEvbqojnS_uH-l>`RIpi{JuPo;6_k3!en_+R7y0LEK)@#E?mU9@-5 zY8rfNcpV8~@Ubzn9Pq%TXQ%KSis!x=crRG^hox#q#JZa`&AcY&#uj3Cwhzn?xELb` zw-vkNzX|Bq-w`i#=*&>OY{jFAhEQieH}^eNHD600<@2boZA>5=hW7 z%9FPi<$hd}dX1nTa1D5dzu{Z(mk`Yh23!Qn<8aPLOdi>-od*77hs{>~^|J%U2r5np zKG|S@7O$kOKW1x5?`AW>;aEl z0HcBJlU+R2_ENdV=vIp6aA_2L4=gbFrR>LDSug0Uyjq|r4f zCXsjB?+EiRD&X*}KD|AUp{*-OLg;onj8bj6jz@`nu1-TUbH^P(9^aK}SVIo4Y6b2g zvAt$P%Jp2?16E+jM{U@b#~Ubjyp2J18#|H)@(QHI?cQluHRX z&#BJkAo>t{SJ!{Byzzg+ZQ>YXJD}9`=x!Gy?|kPc_5A2s6)jQrkWB3hkgNf~=~D$^ zfTuj;nyaR>?3Eq9cwc5cM{m-v#g3oF*WA{}IU)^%3_&#W2n3C!f(CKe(_@T|z}13q zr*S2VV;Gk8 z4FUkFK^Y*PMg>?zMF#_(=cp9fVe=Pe20D;Wr9Kx2B` zou?-~>*vi!;dYely>i_Irdwj$MA_k%Xp}<2X_SHpJPdU| z&zjJ>jyH?~2~YvT{{Rp0kCnWRsq5lA)(!GPgtmnu2Fhl#G&R++i*l;VzJ~JsF7W_)t zI2S|z07a!|GirOBv{8U@@0``^b?RFO9s8Q65)#CKdFh(F0u$E+)<;2d5*XofL9GRb zGQPPS)oWNXK;!ePfp;Njw>d8B_X6?O-1Sg6OQ zPw2Jk7m@v@#z?nq1xO^G-u3bii@aekg>Lm=w_aD3Gsg^@PFYTP=dT2hZ1%4g7SozY z`<$Me_A+df;&+W;l}4W)*R_s30UIBk6^43r-rY|p86E3uT=6>iBjByo!7cr%svYvN z8(5a<_yNcK2D~4^w^x2O@tjh)WVc59RP8E~s-xwGHY1}kC9paH^{vm3J|Ys!0lNpkwRL_D_=_#Ry}wP@F45!K z`)3UkZR(_q^vCn89T`Qr+5N_ns|x8-=3jaG;@Z?RCiP|X7_1F%#MbseZa58&Nb6ob z@Gr%8zBKUP?`1D>5dp?>Poe(+>(>kWNc>uxz!oz+*^I7HFmQKvtW`-*LRJNC~YSitaBZ99W&*fe#uK44@8jLbXnxMG4Aig2PbLo>`5bHYpo-Ed72O;k zGQQ^|@#>4^Zr_Oi0FC-4kafq@G?wyXoR)Z5c5OdSgEi**ebKX&ETb`=xUP?1@muNe;;&yR{5;dZPKP4Iu{)TXxsf%pV<>e zv+*kYLeRAf9hS#fS6mE{nD`)`PDU6XdgeYX=$=-cs7zQDGk_Nz_YwU?dQa>ZdE!48 z>7FQcz0)I;N4OFUjl^7qJ+Atgo>5(&cK*UZ+Fl?g`w0M*g;IC^PUgqL6P zJzvAWvXz&IiL9*N2$c<{ry)tB#{peiki!@vw>~23UKa5ugM344qg_RN za~-Ljjl42!!VrG`z^CsHGoQ+=_(xIj{iliU^vl(au2}@BBFItQIvnGvAJ)5{5$L)# z--dN{vn?{NPBmU3_#@MBzehNBJOdn=52l19>`i=L~!fyd$e ztEuqDs}`wl)-$k?CR1%OCqFP>l>RG&^#+_>nT2|O>SvXBk4}=+C$)0l@$O?_e(88y zDfH+?S+~>HEki@O`I-m)?~+uVqjBK+WlID8?RCC8(4=S*Ok}oWesDJx^3UhN{A-c$ zPujH~3+d@1m%X%YjGMAb1|W}8al0O%SJ6UT&`kNM$Cg$+r{l(p{fqGrO>Lul1e2x# z!)+t~07CsM^yBtZ@pJgY;6H_~W|+%!WdmulvmQx=>{5QI<)6mB0sW(Np?$1q6EEK= z%eb#3Zd1U=WBlvvuh?D8zXx_~Wm3^fNgNko%1HbpTJM9{^J=Xhsq|yXlk5E|5ctk} z`qRv8p!3$DWhCy;wkva#t9uxgbKa}?Ue9leEFaS0Ot8)p+N*wN zr%zZT&~zyPoGJUP2tM`0>Ndj8{^Alofo`UhyBHyqq=C8; zBOj+uwQ9n`J416mpk5H$79_XlBNLQJnSXKdp0?I@XaS_Ljr@G88NS z04*gGo;wAm$*Ea&z%JEhy)?+JTG}#!y z`JI5}v(NZfd*VM5Tj`CX+07{?;_GCATMe`+Bp*zX&(^#b;y$mhc$(Kqu!76ZhG^uz zx--cd##pxGQ;oy{=3^Mi$4(7ek2AH>>j@t^I$%Ja=939<8Eyit^)A(PC?cwYZkf z2{j0m#T2SA(vnUykaO37G1k6H@vf(Tsp=PV-FXogF1fcm&?)Bt`VKLWJ!{{5bD&*Z zys%yCR#1&XMxOFpc-l!atU|}V*p}xfpdC2rk0$ZYhBWB(*&fFFTcwU-o@`MBQ}T?4 zKrk?S*Sm(Mqp9O#EA!o4@tb`-Jfk^{SnV0)<0GDVudY4|-P*$h7Z%fqSpZoQHqV-$ zOn^J{&mj8O%37pvZ6sNV(5jW%NAZ7!dj9~ytxs3dt>c=?c8AD0-+*#hfIA*D+x?pL z?R8`2>TPs=W2@Y*r>bezR#w+SGC*r?08-qRBmiU>_s1OtdKZUac`l-vvl&1^L`{K* zt9tuap8Po0U&QxPOCtI6S^x)<06Uwx{Z4)B*z{p9k(oga!i7CLe!p7ru@9HsDw@8f znG~42^WLIVTmmqA)sk{C+tR5y+Qj4zdSPnaCw6OU?%4$cix zC(|*m?}wfeBekS|`YcvN%<(875X9r~tx)@Z9r#O*4WwEB0Ka0hq-1pJL-oP$Uq-$Z za1~}}0ftA{(xOq2TO?z#H8Y^k2dU)yR3MND+r~}~X@J&&hy$yiN`>VR;ymZno-Q;1=VjnXp|0i+5e9CQ5wlo>RBEEL;PsR(+h$a3T>ln4t zweuaSPiy9Fj_WvzR|l~;Q`-kT;<&LCx%IcH=;3PeX#QTO(w-{#r+45V4%zt3YL_;@ zY(%(%JDcd^mgODx#?e_cL5erbKxYg<&mC*i^*@ZC7XC1P&aba{OF__lII`Kwse5yD z*B5sZDv|rBu&EIzrsF0uIIJt*0eG9m_MRTN@m+_9l6?l$Z<9=lNnd1ZyK}pppaP|U z10a)w&3Z4x-2wbP`!0Mm(2&Z<`yLy~i;Om99(E7?{NvaP;hUuhUXs-GDZ;gCsx_XU zcjSD1@Q+aNW~t&WD&pzpv~zCKK+LOSx$O$^!}IN?NYxMZ>(3HtHxeiv^Q>Q>PrX;z*Xj~L8$&wX$Q)r@h2{{R7T>}x-1d0r03Q>N58 zX0Kz#bkEs;Pw@TI_>aWDWAOH$2M={~b|s&t0;vOPbvRYr$2eRQTJ|0mJ{9mC>(6N> zn3uYp{-tkcI&FJsCY_!r-G7C)ki>Nb$UK8y>Hh!-&Ay9vnw+|A_P4CW50|OyGOV)0 zkHRL}NH4Du~DTUT{5s`zADkko%-OlV3J^p5rOQG|ph_!2-M)*Wr zfTWBL)uG}Kg_fQq@OzoyMw%$gqu^u^Gf=gPja$tikROxN73(@0$9ti)dqFIu6+DBH zj+N=qg5@U{C3j=<8{$o|@csPyb*zOg7I!6Z2@F6W{*>PU-OF{QNTHdYJ==SL3Cj$A zXYe)XpS0)0YrhP5f^9(~XVY#Rg5TY4Gq`pqsO{Fgd%(J?Xr3anS(uAvlgpKTi6i>g zdiYO`sJUvs$D?V|nVv}sW^kg`?;|_HsR<`P>~81%k?CJa{>GZKN8{-2nU!W5bg`U& z3o9ez9{6v=72sAe#ijVh^48gBd3sjw{#y0A(j#H};RUwJuf% zf=?|Ny4d16OFS{RZeVn$F&0R7)lR>VcZ9OpUby-rvR){fIW{1G8h5994xv7s}$#J~nuJ#2yy6miI=~pm(vk zxSk!NB`l&xPH;#}k9nI(N;BSFL>I8JdYT;X-ah8cWE!3lv-YCKST5r?IwF+ zJZC6-_04&=jlLw>_+c(2ytrF+QI*eAT<^e7jepxl@4?>6@XN7C2c7oNr9_ zJxJ~JBD`nzlen_J@hi)zTr8SgId8J>A#NE)NPKb;Kqaxs;YV7+P0Go23OPN0t;-8i zHgVSdId|s1+_u*Jie57PqkL84A#n$WZG-86806F(tS|%V=D7=>VUu1tb*0{4-uT6la(rP*1)?E*y>*<1ngAlfk=?lByA z0Cg;RJlr3%x5PghYLUrrpzAjJd5$vIn)HEk+eY@!U|TpHag3biyWxjPUQ$THt~V{i z%h}SSI^K8WkI5w6y;^=q^#1@Bcnv&4t^J>`O*;kqvzIv?hXCTdOX7!xFEqV67P*WW zEyz;pcLF_)dR(8gKCR(dR^lB@5WM0f`<~ml=B;WPH~b{N7S%L8LgDT&AdAh4?fHBH z0|I-1N|By}BCaxYmD9Q|G%z{EMTCVHMzr*U=jMx-NXa#I%=Aq?8&_61kJ+6yIQ&Ve zE`xV1kBOnPd%Y%jB-tUJF}aW);gAqP;P07=-2&d2C0^^)q@%3>|dBKdN?z!({? zZ`#wXMh-7kbp14I^Jl=~^88+1UDL%=aJo$=qw1cU+eK^n*sFIELjX8I$G&S2hCt5A z^M)UA)kvTZ0+&$kdXv-e6>>yXWMj7_c?^9%l?B2qlLNbEFm|at)@LD|hl@~-(jZ}t z-+v@wy?>CV-b?m(DE|O48Ovs@>e3`|#_(=yh@29{bO-rVGRDmD%Q}M00ppOw4o}q3 z1@8bBkH-2~Dxuuo68)#Tq9mmd{;NI>12p~wBRO7=ei+e$oRrrk*^1(IAUXZ?ob z734n`*FP0JO`rMtANnmSCT&l1lZi>~&0d6Tz{fc2QNp_$oUdxP2nwumj8-Q>Zr>^a z_4TRH?Pl6AeREJkrPDaUs@k@qx?YuWbtIb>B_xnDSyi7T9FB}VKWkPn?#wM`#AeZ? zX&=kAQdOJ}na}rBcRuy--^VR>Jx^Y{+bhEqmkfw{ft-?0;4A38PsX=8#-Q>+6FP!o zg`4iCeY=|ZyTn=}$Ku=DE5wTVt!`RGwojSn1pVR2J4iX>CmG_tb{x{5Jdf022vec# z2BR_&<5^r^Gs?&h-#LlHyrO zJSv0@(>$^KaBGP1KaAmmIdsbt9M_Uae$gaZ*nn_Up7_UK!oI})le{%9lknok>l-fh zwMJEMydX^c#~YXP}nwMLg*la??;%67NwmwPtdGJQh!a6RZmR=q=aq1Bmu8PmO=0nvP zUxL2F7_Mhk{hwC#8&A;w9?7QL$i&IyLmVpE{_}3h9@)noE9(CMh8{Zb{{V?D?;^LJ z89a#!GW7g${cF^98_NqT5@L=u+&c_bYNbv2k5*WES4)!j>U;}v`z%>_U&DLv?W2n8 z8S>*f0OO{6*T!EMd@y`JugJJ6H}Uz`>Yv0L!Kt*1xD`DGetiDd`b2tOt)?;$nqt}f zE7QQva+T!I4>zGsohwBiW$@!$YaLG6o!CRXBY=7Wc>e$z-|-!i=)O9>wu_s2m`bbE zVe)wT9M_)cle`K_k_kB&uR^+=bxl&yiOjnMK>C1vez~todLC{O^HWQ+J)2GY6rK>! z^>}0g;?;$u*f{5+=hFnOeU0${08;bx+gn?QEPSPwCeI8RLHxnbALC!2dOo2gsfs2c zVw~nh#~YD>UOu4yb@#`BEq>MEjXG689U@0ubvPYA5GpA>NXM-;JGr9CCnqFTc8p+> za!-1=&%GCE!jK5asGR{AIpVsH452db;kn4hMSVr^C;mx}mDlf1IsX8ztzR-o1~5f^ zJ@7bV;jWfH+ME9XMzvH-=ds?=MHOZtUU%{Jw)`#CkNa?c=;W_NuRZwkyS^9dp!DAd z{*6j#50>l(TiBirZQ3|sR~Z7bY@)<@^gV@c*+dnHZU$>aG))K%a5%kl@p*bDB>p82YIJ-0R{{Z8CvRezt0m07V4;UqZKd3*QZ2thkIs8=?i}4TQCx>Qr zNv^G}Z(&ycFD;%n{Dg^8{Cm;e@AUv%V2TNudvo&f`Q+En{{Rm>T_?itk2)WSWMd7C zs`mG#PB9Y*&joLVwn$>#gUD(@(W7WLUr)oYx0o@gM#Y%}Y>< z##NcEl&_i970BQdUVG!qPY`&EM;3Zy!KasMiIn`iN&Ca_=CFJ#@gKq;1pGY(uZgb{ zNR~{oYoqf_{{X~u+}DdKIXhhX7{WHZR;;1oe;IsLw->Qrt-LVC#baw(8b&MXNl-s3 z@JpWt{6O&*vp%3TY2)7Hr;{3%U#l=R^?H1K@UFicH#%%EYBrJ$!bwTlBKm`j9=^Tm zuD$VpPr635@b`zF=Ikcsj^5R#f50zlsLtA3Q>9X?@mk38uZ4dMb^Rk){?yj5rPMB( zFDx{pJ6Arv$?smN2BCkVYkG3WFPmd5=@juu+@i7CNIt;yt`zvc;;y+Kbe{yRougYl z(p>65LWVVL9ybyWdJJUO&$_3?e~ca|@tvNNWvAKOGwhm4#^V$!er&U6wmAbeF{e4o z??Wn^INdkpspvK{+-Z>bk4sUt>~HQij=+zY52k;ebKVj0T((;Ex-)E9*hTYy1CC=q zfy(_2dXzRcv3Tp^bQdZMyms1xDePoWP678Oyd%c2n;mN5p>2w#Hn*dL*Ym2rtsJpj z(A4@zT!KFl_-;cF4I%~^=bk@aarG6;cw<94ZKNfbq_2Kt*qP%jM^9|$KAEl0ggTn| zvp{!|MoM{wSQCSi7+`<28}qK4QL!E#vAUgY{Iaq-5|H%E<8 z`>)NNJg0i#3>EPv!Ru4d&} zNJ-#V&Q|#4>d#J}!o3a64&;VRp1fdH?;XG-7B?XB$W)(x2>!Ls>63YKa(nSzSBS^j zJT-49=gV+^r}e6f=BCh|l1$@+lfgZE)K?*7k1N9uT9jmRM(SjsV|M_a)yiyn)bK5@ zh&5Mt7kE2t`!rAq;HiNH{K&GbB;Od*0}1c zR!#Ot&|w>v9?PRXM$&v)0MWX z{ypnH3-KHHUs%qCBipUTowCOJrC9+g`}hJj`@r;W*%kCZ!2K7({{XWlpLd~Z7Nu=9 zD4lM#7LPKv;&U8?a!>~ONa!*v#&zF?p9Opuy_iab;b}+E=C4B+8td3y#r?-Eu71{5vRub)d#wGwB1~#_?L2>BNfu~YZW*7rDcA7n>s)7xek} zPYlWS?L%L=c5BNwi%-3eD=n0atUS{jU^Y5%PgB=5-%f=ZaZ<75RjG-sDMBw^$DZr{ zJ<#kYvW)8Qde0cSkI7alrTS&TAP_<6#X)!C3GUQhTNv5kUot}JwnGs(50G%`PZ=J( z*0s;T^ze6zwHQ+FVB73gX9PaZI(s7w~7n=(%9F)Qcha8FP%fxxe-H9aib zYFaOVG})n#T9Vq|PY-l(vE0h0M=VD?JkD|c$Q2FhXEkMG+ddF@2Io)ktTWt*(o5Gj zPFxV-8~s?vPrHNv00K4Xk=vvZBC3T7ItsN0o-}P9!oW<^i%27f%spJHg)NVKXYr(f z$FfF~CBKDxSI*R%oSd1_7^tfiwyN{_gH-NfRhKvzVcM=-vJie;5y&~_sS;QZPkP9r zlYoqI&{Q%m8z<{l-9S^3pRHCZ2_)wgWV7if%X~TTkzSu5Nr)=3Sf+PI2@#Zgj(Bup`p4*TH@X@s5`t#mxaUt9!YQqpR7+w(u>uW;10K ziZczP7$gJ7Za}ZQe``yJi{K}TV`(;d{!C19&>2*oze@bg_;YlF<8Ol`f7~XYsMzIl zPSCT(za;kohQQ4TFG~LZEa>E5u{<2Lf`?659M8Ep?wF3v_}vsD2-2EGHc|I zjb8(NYw?dweMvRgr?T5G*&wz?Nl}kyCm2ut9%er+_f~rcg=$06)&A zN)cY;ZJiv`sidN<_n$`(i58m8xsT6Zw5a)@VgnDtyg%ZHh?X~%SSVIIMm-OD%5RLn z4Ruh_+-n+L%!)`7i-lKDaKPkM?+|!i)5M+({@K&!Ys(QIn+*H+?~gbKaNzUby=Tns zxs56E!uC9lH;zf1f?F-n_pe3pTebvE&ln3{WoF=A1w8Z5JuB6`9*C`+uWTPtUfmaU zW6Z=#>7GCPUwB*XJ^;J8Nd9(o1CM(62E$K^^7`U68@EQxySc#tkUvf<^(*#)(xTNo z1t4_+QH+G2_EDJs04n_4@YRGGW8Z4mK};~(e(f0j`CVBMW9oDGS7OrVhgEYl&f`+l zaiI8j#PENui4ksg{Gc`rZUG+S{N}wE_FTC)U$jPrA!L!37A{CXF)OtGBsX7kUOnKO zrPaI@s%dgaSI9enC-@|fjy;_-_}8d@!lkuuj~W4QnXTZSSM~~_l%L0s%CtFKzNhK6 zjE&|_LKBnJ57Mt7J3|xKj5QWk{y-QZNgYRi2U?WIH{r<7Vb-)V79}P{$v8jVtr!MF zWp;tUKBlP0!vY3D<27NWV0j#8pMEF=cb*S9@TR}zj1Y$$ci3wt*5M|%5x)NbF;{RW zrhb*H;8tk-Ev~UVg(MUH;jAkl003p2f&&xH1eT*_P)imdbt~GP8A&80?_fp&ZvFF7 z#)c?%vl8mr%YTJfw~gc@7;Fv1&;yY`kiJef?ZF%h7I{O&OAUneBb-tkZUhhjIr`Hk ze>Mpta>Oyl?BnTzC=ri;;9WT0YWHd$F{;4O-1$IcWeV?K_PPBl;-47!H^y34lc;$N z*ZNMGm>%>YLecKP9Ii*Y=N0$dG6aMGzzkyspw+ZXe-UX~g|b>Ku-wJv+*>FaVtTTB zj=1_)k%^-yYX_#fd7q$g_Yz_}hc#d&r;eAf& z?tDG0PIkbOF(ykn9Po@AEV;%*8v16!+<9oocg99{uPR5VBZ}vx7R>W?>~S-#4PjBa zMfXkL?^{W9X`|&0WA+#LTYq{kt^6#u^I!}@@+NW9jN-jdz&`}^e+XPWwwhVCxu0sw zGtAD?VB};IjOV?3EXFtx$lNI8vEUEJzIFKd`$xxRZ!d&C9sdBuMdMrc7Gg^i=0#v% z<=oCbUHx!7a!*RqqO!c%$AP6=9Y1A47F}ORuI=<+@XJ%?Pl@_=vGHH_mGNDVfOPAP zR_ZCXvssX+f;Cv$N05*d7E%X1%f7H^*C2Qg?-8KgW}hOQ%;uEyh)^_ ztO&>2M2rvniMfx^3izMmuZbJtjqab|&k0yu&kD#s%WviEpHaMH_sVC1jD=Ik1e3`) z=%w#oJ;|X;t_Gz%!n}D^H_Wf6G?uYTzP7!#S7*F_z<&p9{7t4!@lV7SW_@DX{!48e zE><`KrrBiLIA+V01oXkjJdd;|ki_gTIR#I>a-Rph44(`>6L@FB;3~^uXBfCBavFB| zJ2yVn(%oi4p;R=0eB9@DP6c~Z;HkwZs~-oB#^N&y^2B0h=O@+bLo7mA)Gio~ zIBKN8d5WQSlfyCSD#FIr`9g6v3w+od)E9V`Fsr$PXBgn;uUgRHD>^bFY~Mtcw{ zfa-h#Ytj2^Y22rC)( ztWJV>h-mtC^sgxR(c-Brt!^~P5uP|!DeoVmtZdv5#|FJ^KnSB5Vl!T0<2^Ph{A;Ue zcbGBj`dW)-bHS1lL#997Wj~3oY(#mXW6{7(Q>)DTe_w^qB(Z1KEUY|&JjS<(l|hWQ z>=M6*GhC;{T^1|tcH-wvvqN=bWFmR6`}UK`QluR4PJ3jU?QFCs@ViM2E#@>#tr!4r z@_UYW$s~_z>nyFm;U3WLbt&VHeOBRHlNe-M8l}v3 zo?JR`jz-<(JHn?6o_HkW_2m24=+EpIFxEa6=#yMF_tRpM#AmQsSdY<#e6qg=^n^Np ziT>5)T1?WV$dG)ygApSy>PK!kuc<#{JL@&@H;7}>;xJpQ3VtE79pJAHqJ|ui2wfjtd zBd~>`)*yhwWZiSY*YLlxBMi2Hiqg~`CB8A_Y@Ich8`+A9u{R$)lB0objGxWW|>cvtGli`S6kqVN50hK zn*q^s<2^B)lTFs(w!9WveXbdtd9t0~aYs%){{W?QTVe3liE4_$CBBWmY+#}mACbTY zwv?`|+{+6~mEWQ#vq27}8cC5Lbt-Yj3mlKfHTSo{4SVgL8?~^ykIBBYjaTR3$sa{= z_zV&1J?r5MTf0l$U+sy7j0ha6j(9k14{T@gueUq_acM4<;q6gM$9)m|9nvYtVJIww zdZ{5wpK>Z`=_4F%nmumOv223}0AOdmEQgXn_QfT-Fi@oJUW3+#U8M87`PWh5m1a`v zagoh^J@7PR;ii}V^xyh5tLA1rf;b-a^xwe&kA~V``_q5u)~ykY&hm;Vsxk`TemSo1 zhMJ)N0BRro8nxe72l2RP;l8Q<^gsGFX|2HdqfU$<+Ic3n;EQ<9F&Zg1X!_hT=b>hM*X)(?XzLyvlfv4}+q^;HnGT;Rko?oa zhip>&x%nt;J3wiJaMB&?VCH*`6soI<)M?hpHbW% z;|9Fi(B+prc0F7zW|uEiS@<{NEhpg*hSR~5=vMP-mXgd8E0R7%l$I(OgU0L-Pi{L3 z_5EAp=9Oi#Z8{AS%2$hIvP~n%*c^a7q~rshr}C}~#J&)=*Hw(r39>k4;n(PEi@5kd zG`uICVLcVkZ>>~n)JoSqS5Ggj`RhTa*=_m$hF`>gjS}jbgjRZe+v@keOt1rM6F~~2 zpP5R7$i@IIlgF<$h2WnIt&7BGMKa}l#YMt^IS4(g)U=O;$zf}V(JhG|G=OE#<5FsV z7q;-;lO&5F`FYD8rn%+J^=7pz({c86A z5%D7ZBb=$rw3A>U2X0RTkPhw$_pfsa{5$%eHH_A;+*SCKs0(Oxi*YM4 zh%%78p#nX_KaMNwpMf{SR`^TdtAOG2Y*#+JSdZyn2>9<=k5tty*cbC9wOIr11#nca z$_Kjl#})P$?1`zHuY-0L?%R#Ku}t;Y%y|C*zJq>s=~903^gN2o-T9u?IsMtiRelES z0!QmsWWZ65bInv^l5t%}83n-}zlBes0sXh9V;oGp)f<7y&VIFH!_AF%PapKzXafV{ zVcX+fMCTvs{{Zw_)&@AIylBoXxmYBki_z~i|y*uFUtvMfSn%>Fjk|4J%ez?k!~^`MjsO zSqKRj2LP`ijllH)4E4==H;DfLXN@}YYh6f|)Nd^9E+K|F00KEA*j7~;87Z*vNXTQz zuLjbsHReMDP}Ckp4}_y?Ki~V5H#Ci2BvMk)dB}kD^9nJLyj1(6XoZo4RwA2)^!gRL3wqq z-%oXH8CEzR;nXKm-zXy)r%rLFw7(DdC(*dn<>%y9{{R>K266uYvxmVuO(FH3~Zv5Mxdxc8%FDPiOr$zmGADsUH5dH>hKOcT0c#~hyV7E3A&nmv9s@}nA1cxL6 zx>itFV;EfH9QxOwd^7j~tY}s+SZaPZ@RJyuV#i^sJ=>`E^3bpASUxlO*KOhz*7Oe% z%WDRy9G+#B?6!*%h=|XWo?3-Nxk34c2q&DcJHG*cv!>P3c=fFsc%vJ^8nwPdaoc`> zO84XL()2t@&RsU0vNok+>_?7#;VqQrQD;NnV6zy!*kLt@nz5X}=F@AH12aHT1h? zBRR~Qx%wy`+*KV<#`>qlpNKN+8n5rK#H9pCn`7KKj7BrU?brhL#eH|-p9Od~;f>ap zsGSZtyhUwg9lY0qMkS@&i6q!g(8nZX4wc(dr?G{lt7!SzE@@rtdd1w^+~I~jDd`+( z6lOz^dE=VHv+*U4p_dYf$?3dewk=s^fRM`AJTjiO^X%wNGL_jVQ3>g57|;E)6^`;@w&1Yoz^z+?Ps85|u^XH0v7G+^+c8+&=RBWU z`c?3w&k?h=m@j-{tL|{Q&N=8i)W$-ra=S))=dDL7^*xB`R0V5-8)*l>t}3bh%;c5b zyP+Mb!!OQA0E~S|s3t=p!(*X19+bfOOZNTo@Y6gO;olD1$iHdS^+>KHje-9FQEUvZ z+#Z{RW8bBGL*SnQ-Ru4%ypl-ewOgx$15Cu`-W0@_GLyzxRBZnMdA+OO{{U;7+m9c7 zeik-LZjO?c+GUh5@_ffWWW~F2j2!d`Ymf2nr5}KF`z;pMMSWW4B#Q088zV-Mzjg@j zS+~D(LXY9EKBY$G%M;V3O(=6n`&;2h$DKdppTn6R+EBW-oc{n~)a=R2#V8*ud#kP( zA6>($n%tA(M4tx!8(Dv9$1JzEx{UF|91)j)y@gN!>T%k?F+XO1jJH1qJ|kXuiIv+z zmf|aYP6gz>vpWLA)sW%G(2n)`)#9H6cw^$HhV-pbmG7R>;ng(ux4L+hrCqL$3K5WS zrw4<@dDZEAI+t4>z84c2#YStd{4vYwe+51v{9Mwl?zNqN{t&B4BKtyppA%iLIP%;P zv>cr0CmdIv_^0+$_+#NsI?q}04bA@mh$n&xQt)b*&e1!zLbf?5|&?!9k zue7{peWz$Y4X^aAItcA;VMKx$;y|hqM*t|`4`EdNCGhIUz#24m))5F}1LrOGq&>+! z>yY@7sI0cl0?CEsk)926P0Fj>i8v>Cq`eOaTjjR9!2^??f0cTFgf$bj7%*i3SCDIx zM%ThL=PiNx*LC4Xk}GJ&;tO-f73@*bU7lrMdqJPH?~hYM_(`ge!|hYX*03*q@+nWz zOCQ3%7PGZq5oiZWh=Fk!`$6?2bRU5Jb@X5DD$;A_+S%o2iZXDZa0xt``Hx9^-wbQ1 zs6x3hZjhsNWdP(?WOY|Ox|%z5D|l~I{?EI(Boz|dG;9>(C0sE70NI6oSN{M6-|*nn zek6FSRVX~WI}afkb}~u{{{Y8O*U0*k#Se+^)&?sBIhGTTtJ*Em!tAom-K*2{B=?PKcMn(rY z6=X&ir~{1PR)%7LHz{6+t}4W6Nmkl;Zna8C%8$GNJYbSI`qjmdtY>IB9AbeT--3ZY z8rMO`E9w5hu6}5m0?2&%vpnU*}^lxL0ywM_yvab@NCgJgHW_n?s{8#bnQWRb^V-kT=|Hp3Y6 z)kie(2%1KJH!Ge1Jk?p%)?b%92TU3UPVJOejkX|QpgGP>U9@@aq}>vY#ANR2Rc&XB z$#jz}#Dbt;@;z#AI5=(q$4pX`RF#?k#RS zQ>n_AI>xT%M|W+_6j}Kr9)J!{xv!z+SZ*LFLb8#94?-&_LATD%++IGlX!{AxxcdG^ z3|}AoA97|*H(apPb_4$a9@7RR@UNS{Y2Vt9Mbf-9unV|R?<6t#kH`z(1F5fO@qfde z5L!(vdUO%Zo#4ba;QEYoubX^b`z`3+C4uz|#A};~i+O0yN=BsQg&hTHCgklsjw(>6 zO>e{uPzN2bL z%H2i1ljwVj>u&xUXul7wT0oIR0pyYfE6BW4@n+KM@wCkePN8yJZXxAV`?o<fzrqn@`EKd$)}|JEdFrc3Yhq($da36Cv#(R0MrgSA%>GONoDI&jQB*CT7>I zhX?pXnQzlI@0ve`?z|uHHcOp$<8{@*X_6e|Mi_n3{Qm$N&i#V^6iwo#++l^ve3x;a9xUICBc}sSC~BpL<=z%Pj5<@qgi(1GT9|}4xDqEjh-Zt_-0_EBdMkZTib-+ZxLQ!fJX$@ef7Vc z3r2-nL%mk+rMWl8eef&A-=_`GxR zOT?YO(m>Cz$d#1MX>N1SC(XN&inxR{W2wzkh=QuQ$vt_iF*eiF1J0DU3@=|Q|vdVtb5fy8gI_{ibO|Y26t2*VF$?K7y)Eeac zbFM4bjLMJvxETNbAjW9}|2z;ka!7 z0O2FjuH%Zum5Zc_zsh28B=s0?l;e@_n)%3k+8?Q@s4Y?C9zOVwWu^E&#>Q_6M>d^t zhB7>|myawrNgRMGt^pq|3EX+(gJbp-@%(-o_`Tx~243AX&}-J;X|kF|&zmd-xX-DL znEwF4YsoMF0BKETKMl*_&0_JVf0_m+M3&A`&N3NJGwLt_?7b_@w#hx9V zqPo+rR^}xHjf^pnS0wCUcAOG9HR{6(`6W%OU#ao<%)&CO8nJg#dv#s^0IrAW_s4Gr zOX6P(T*++ZSzsW5IuLVS9q^*h;_rp@O-EYrhNdjHHu*H=wpNl@Q2g&39(O3`Z*k9K zUqO5y_@$!!a_|+dv!^=wH?b7BwPTjIn;$%F?hocLYt;M~;22`?nYNF8yQ>$9Xt;Qs z9EMZsKbA##6s0Ih!btXAN^**udVY-H^sfwjSMi^Rbp1z8_?dBg9q^3C@Z2K2sKfW9idJJ{%n)S~S`1?%oP3eQg`d$8y zb_o&dIuxcjr6du#qd8sN=eITC9zO9liK|=R!hR(C4d@y)+PO^GDPvRz!N^!4i>-l03D+{VP7tQMb}G!)aqUd6rE3~ z(!$$nGsw}*md9fwDzSDTaxw;Z_3xZkY5Up}S{8!lKDF@fziZ+>A`AN&R(pAdRfhx- z!BRUgAc8uA4PKDrX*egiubg}Z;@xw=I?A0{QhhSufpL2m2_l{nR#CuV(75_A=xgZ6 z=~%QL;AiYkmkxL=K*@=kR>_o4p)(W_n6aDN+)--h~`{{U(q{Tj5^ z;C$<9!3WD%5?)mLn#r(z%gL=M{%j0@2VB;r8kWuuG1j%M*e@r6j->Rg-9F0Z=}TL{ zWK|h5Hv{nXtqA-%cd5sfSx7(K`EmKy60H@sriu;fKH~D$+C9_U#|nY>nZVD}*1Z1! z#{MExpkBSIO>ps}6_rq`5;LAoIp?iQ@N`x-mp1W4ZM7I%5g<9*+p)AB<2-%>w1el3j(VTFk=pz%_{XRCrZI0jeV+C; z23u)Z766_Y5OB(I_l8H%@m{z6vt$r_>x_0a@)yUig#IG%bXHz0@anux5|_BQwoGmv zS>yC!-8vEad9{znuN2FtM=j1~wPF7NAGVqKeRs#yd*e8)+*}=w`c+j(-*fJd5_sCr zOSNY*uFyN0`J3X;$CbKfw6&WtjFLg?fuHGKIpQxEc$ZwZF9xR4K*J%I4f$6YrRi4} zH^xh;WS&v`mUuj?0cz^~`zdsg%%3P`8&cdyS+8YJ_0Q^Pkb-!+ZYsOV41 z1_>Xj{5h|){{UkhW>|bRDJ)H)zk}46+0dXT{gw@k`l$7;>QcWeJi75|$sb@zCRE`3 zr>C`2X-?z%RjC7k$Z6!hW9#zp`ngNK#1m2y(@@^%wz2 zwHL;(h#JH;Iwy$#0I;m&I1*Y} zTg2?WGq^{PD|6zmk#%F^Uk$yD+>qMp7L8#%W!R&$j*PkIr#<oIO^d}4 zSXfz0BzBh9?I2PKEWup~+yTem8BxF_S2Y%+PVrY~(btE)%OsRm`YRuBcs6_Od&1fo z*4ZwuEUjTO+)MMb&J!MIJ?6`7YX@74K$vZf!9&O?>;7?GP2%r}GwOQuX4WRSwF)16T)5-V`d612POEoEuZNWi zTFu!lk@D~DOW^yhCjNFZ{M!%Hd1&-v|N zOGPzJT=@)5Wh&B?PoumG@dy4A?+?jf?d5840A-0A3nKL10qwxZ?OaF1Z6z%sxw_OO zK+~~YV>|P~10T#+B9h#AW$f>*WQ}EIkjEq$$s2R`dJ&vwHEHhd_3chcuhL1|X7D8F z3FtA?j&ba1MhY^#Lar)xsi;iteh27HYvKjEhA%SPPF0xq0EWUbC)AP0wS5viNcO@@ z%}PJDxj9|W*14|-ctm(B;NAW0%9!;XNh7*&!{$U*9$Nl6B>w=tR%~zV?rkmPxK*79 z`Qs-9RuwH(w`~@Ok11MKxvy#Q65i%=Wq{iO_d@b3tsb)TlurZ5fA+I zkVc|oKsA9o(KCe%FS@myuLx92yV9m__G&&|$jV%x4}30oAX>(G{{XIHum#2?aHMn@QQEeP2KaN~O}SugBEcW^%vL)ngz^a_ zabHUn?xTQ;O_K6P~5C{n9t6E;+)S zVw>?-!3caR-Y2&OAv(NvX#0YxOIvuDumJK|-MQzdy>99r8-E!18{&=JK3vafZDSIV zorPB1O6;JY@5|KiaqUHu3MJpMRq}d#n~C)4URu0k z%=bNaX-}1GVA^~f8c&0p%#0=7!^eAajDBQNa}*xZ5s#|*wqklHBGkc$j#TB zV}M9pD*pfxt~17-J)g(A&BVHHmJ%3j*oT;mnA89WQN(H4K{+|e1oY-|l}pA)SF?;P z;(oZrp;_xNM=@2B7x{yKjYoBBVWvd>KtM-OybAb7_EY`0Ec6R!@Gp$DjmnCj*?OJZ zZ6_=9TgchQLj$pigTqC6|u5&lsf%O)osr(_-g2>t2*$ZO=8-zQ$*Y1e)FE*??|O zIsX7XDy*Lcj<=#oacF_3RXi}q1XPik^&MUuaR@m%?_Rs$oj}-Mv@C=#2cCBdsXH0R z-g=)2>%J7!2aVH9v$d4o0~~2@B4PLM+7s!PQTU4ef%rM$8$SVjHt^Sn?Gwwlv9XRJ zxD2xqx!B{mV#o2W8{y}|uLpRy;uXJ$E_A40Rk4BE2?!Y8NaT!iKsg?tm3!=Zaz=hs z3I+yyis+{9u5i^{vav}M%99}FPXwP@v}60n1pNg*KsOa5Is7S%M%*tUNaH-#rT|7G zU`H6uMJ%W}~+(0*KJiUe9^AxKlSw_f!W%FKgnd1t0Ok?T_| zZ6H=(;T+`lrI4SqoUYXA$mi=pB}jbP5N#zT2N^5DrJB}MJEYpmcq2IH@T-tpAWY=3 zJm#ffGRf3+&!sRkVO9)Pok=IK{-K5yZ4eiV*}c+*l2eez0!zq zkOA||%Zz$~>SzKh4HoBJd6h_vDjlrDjopQL*NkkXcZ}Mpqq=^RIukv9{8! zmK$(DToPF1lj>`O_`j#yy@j5qa&}t7AcE#q>k2u-$bFTupJpeub63K9X!A#Z%<978 z-5K&rZ^-gLhd&8)NHiGWkUL#Nxg)xQSBga$Bw&Itd96A0Zy0!TY0|^Q_czco;utju zW08@8?%)D=^{$6RwwuGZzD>dX+aH!e(EkAS{i~~&ONUpC6k?JA!!3Ccy+3uILmJ7u zwRCwdq@NkDtlg~>!`D{mnI>jv+jpip{K5Py%RFmu@zYnZp4?q%ejb3X8LZUHD-Uis zuc16aW#fG|)#K693!LW$N89>Wka(X&_`j`45@~Go*aG3&92P%`t^K7w$89RK_i z%=nk$AHt1LT)X(A#TR;uzJJlT<9Yu8cRUZR9}RpXr|7z!vzt`5w28M8M`7I8(DVEe zxYMtvzt(QP+b1NJ=N0qk#$Od$XtLZ|+Q=b=Kh`q!_E0@d9PX#Mjyy!;&FvDhJ6|1q zNw@f&u4(=pk5L*nfFww-H6})Ni8IS>UQRs+UMudugr~r|PlGhg1HhWCh31)Jm_ZEc z(z_m7Ne5lba!JRxKr8Xj!rm&olT*0V8H{$pc1I9A1P2G|N$P9Y^dAx3>9=uQTRBHl zxm^y{U!x91chjb*#Uy<7YOcJsKUO7dN&_}mJm-P$RTlOq+|d`&%Jzo@bmVM z@m`*gM|AC}Tc!rvp}n!}{YUFxM0h9TCW+#(kSl$H^~fGX{{X~)*=~pV*6K-|tu%DT zBG-l~z}iMZ4UA`}H5{=Bd6q@<)a67hc9rKDJ?eRw%Q2H^^2=@CfJSP)(NvXBl)FLN zc8+>gl2N;s7~v|ro>>Os(h|ob)6%HTC^79SIb1p0f^aygCyz1DB6E@eE7W^bawGkN z&5>IhKvu^&&w6NO?}rH+{6Nv?$ywTR8zTX~cHKQOTqni<0QoAOBst^lL;nCprFY%| zhD&dWS}HjWx%wBo~b;~g{Ju{sK#A=Q&a(k`w*X7b`@8$c%@XT5pNj;S4{nD;Wa^CEfk zuU34H1HJ}NU>AYUHRv8Lgx~mb^4=m9q){GyH!uYLx%?}`Wu8r3Y5|pvoC_VDqeQq{ zn3hegBA%Ux>)O1Gd|Z+~rzDhO+1lLeZDrvPJQi86U})lOeciz1C>^?r@o$Jm?K}(S ziCQi9Bs!@$aLJLo>-_!e+&ph%X*Qpx%WEKx-EA48VU8U?gb!XT%XJ-hM!V6qTMMZb z*+99m01@1N?bz@z;GB?nJuA$o9$gQ(=jV!&J}dEktdnaIq#*g=86?<&RCXVr89mK$ z%X2#3eVn;?w-pL~`-=5n8fg=18pX@(*(;wn$w9##dUyW->t?+5bQyfxi@98=MGe!I zImQR|ucf5dDnB#FL8{K(&!RtJzZdGh7uL0LYax=|{I-??cyZ4-?8DZ-RsIq9?@sYn zkfJvNLHFY)45z+DepPe1oNp~NY3G5gj>rFmwV61o3rz&x^ zNnIV5m++HE@btyQ8-kz3C3&~T{{S0l`YxLS1{eT@m8u@SHFOBZ}VR-iwu~^g}E*#___xJa&LX9am%`?r#)`S-%4>S0w;|q@$ zYeaI8pdvW4_g1)OiS3w)7j6LK>(aKaEe-F8L?wVSy2PcA8E^i%6rL=D%hs-~x2vV3 zzh^F^0hw26KbWs>IwX&Zs@$aH%;i5UAwkAD$?uc>FnH!cOTNQ z^z8}ewMmK{yT0~6&-pdkd`IxaR+rZEY3NqcSRs`TFb3pYkHNpKXFE$n(!#0Ii>Lq@ zLFT@d&q(-pZ={_P_f(GlIPYVbV*4)e50q5rjPvsjzV-AM!b1k5e<2T<(i~b(83-3R zVsqbsxfnU;iuljLcG5wuiDcUtjZBOP7zBUy>+KJMu#5iy30li_43Ns#A(G%@O28=DAC%^ zRAu`!l}*Q$T#>W>0#t$Rip$ltad~;ADyg#S4rJT;}8RnJc zBzhJke=}WiUiOEHH|}a_Tu2u@s(#clk1aj(T;i zCe)#l%IZkuSrX})K)rFWlvM(PmVqnT|33bBt{X;jOcx_pZ$~{&(@oH zIo50~AeaUhk(E!E0LTy(9e;^QU#=_A{yoJGsif(8qNWUc31TpMVAqpK%{bESpN2+I zSh2wU*%%!$$RD2_E96_`oS=`er|;8@p7uGf1?nwjtlVjH96W`s@ZA3ZyZHYAF^c+E z;lN!n-6{L{}rYaf~;MSTJA zM&;zwZx_tokm^QAz-`4usB%7;QC&EBd-geTkzBmU_uq;ZN#Y-bz96-TnC_O*t}W(M zf|5t`0txTO^RLefm6J!k7v4a%N!Wd|(MQW1hwjRw`>pBN=hDAM^#x0>1ZybcJ8b1Y z_~8}vZ^uu9k8R=GJz~b($t+eV(?W~Hu#uPiRkBCpUX~^fPV2GfVCpDn`=2~r+FHXp z$!CbX?qrF0UB~!Jed77<{1 zVnHL8;9+^^@~kPYOZkJFPvKlw#GNv2 z8$^Tb@sMv~F*7K~EhcmI0h+n_JZOAV`$bsYOCw7W)$L%n1xC>ra)aMEJXf)NWYFGy zPfmno;)xP4r0yZM^Gg)kwfh-iRit%(2xFmq54-XtSRc)fGlN*;2_g`>~EOfuDSX-oAjky8g`gD`@~_P4}_MFPMH^q?RC&)9#O6 z-nHajEwhJC(&3&bP>{T#UC+(SZU7u`KYRMurAk(WBjkCN73Vp5oc;ZZ-F!c~afk95 zZWNK%bY)2WYw7<0*fQ=LtrJ_(rz}myvO4z8)1Eu$jQ$n#{{VnA{@Bq!3 z6zy~BM}NnI_|| z!iuYRDF{h9G@clpPl|Mq8zkJVF&^QxZa4#;PCL_p#WG1&ESAqqo+-h%41xL6@({F) zMS0)FAC6uc_*RV`rEt^g8#jwcIVulA=lDVV{j24q{{VuE_w z&ny0U_pBva(&da?pIdbGI-`ef9P^Tj>3+V4-8rQPHS@oKKW>kPo;A6S+UELQ4rv^s zNp`t`kEfWuKO9%kcDFFz+s8e;sXP*>be1*@tf!#_a7VptnrAzUin}GRJoxW7ha&iS zdOSy~>G~us#kJO>aIheo2Wp0522UgLt3MR}Dnan)M7f&VO}X(FvWdDKBEtr0KDpoy z{-?EmX@1cE0Jjx}qvG3*V_VWKJVCDLHxFZ=_+N?i>q)>KW$nWp`OX{UR0A1ObBtym zEnCxC_x`#Ty`>IX+jjo|f!y)0+85&{rLDD%uZ1CuTWOavNpG&i;ofps;6@0-h0Zz2 zIL{UG?esdYi?utMH735)^=Az2B!%Xbfz+JjfIlH#;qW)W9xM3e;?EG<8|y6&-d*~I z-OQFu@md#TCH;KQk^cZ>>(7ar&GpxYJTu~t53CVFB^qCf zu39JxmkY8fK+3Tsa1J@Ir}a+=d}8pey~U=b@V41+9o-iDPVp_QkhzRy$lrz>dh=Yb zz+VgL-U8LNyIo69w3uEvR#t^%Q-hUZka6^{RPjRS@@XX5+AOypX_ob-W@aliqim0Y zcwz<#?_8DVdb%a|f0I3|CKi6pTCJC7(D;Mm7mjt!EI?0(tu1aZV`+K1Hvv9kK5e*M z@Ol$m9iE-4Ytp68sc_P|ljXubR8RL*a6g@W1>@fZ#d9fg1dqEQu*T8sJu85^(*n-c zkf_`-G9p&2V^d6i(HD<^l{wc!09?Rss+?ZdsqaVUWpob3aa#~#1Rz4PEl z!w9@rs~vAqh(4Wc%Pf(ej`$lR_vw@E^{*lDSBG^Qoh7vBAeva^xZJ3jzy}!|bq61< zeWBqE6nHDac3Nu$Tb;gj$xenw>OOz~zlCzvot2jC#!}^piScIq&*AMtHD*#m457gT z%wC_Bc(K)Hw2g}GopbkJgZYo}uSxiWer3}yz!@iC0DrtI%L;i=NYflB_pK;K(6QuH zcVpz&qnM$Wb-vMnBpF}Ke}zb)96Z6pFYuH(2Dz!O4fW0x0UDkKLesz6{{V9B86U)l z71LuQ(tI?(W0ZMCT3l{sZZ_9MZ|AzYRASBtB!iGE&-^nb`}5|Ok3YttvtF6uxY-e! zXmCjxbvgYFa#fABHH+wP=w5!KaU3g^iBBMRt=r)(oyx-q3}2%3=C?ctp+PZe7_RnX zp2T~8RdyW&-gufuQMn)+uzKS-uP$v|?TWfSl(bNv4168u4X(CO{G->(99CqKW9D;= z50rY==Aa6A8^Zw<0w9b4dw%R!JYz0cu|Awvw;zQZn_O5WBn%Fn>66F{kn5jONQ<=X z-HzP%p<@7*AZPsZR0J&=u>=sxag2)dABr9sUlwWFj*V~&Lwj{3E}&!;dq!33+;;b` zQfT*lx#OT9RxgP>IW7DKdtw&qJQKL>4YcJ>?ty{M4^But9ECXEB|+L(J^}rk#m1Sg z_@BX={@5V_u(^%$c6@4PcQF*G~ZMf9$6zo;q zpDk2<;+O|-Ky$d9@I7zBT2`x|crCm`Ev(iWzNLKD#l%}y(iLJZq>eATk0UvWRYnPC zAOI`pzlxgMORjjUGm&>9$lD7E8P#$E7VouHK*#$>y>Tj!5nGjPzpv}e?@&}I^F7~F z%4Qa}VpTB-i^fUb!~)$$KPvqp{eZOn8(jEJBi`BCYFA@YouZoZ*(H_%gaH+p5&*{o zJab=}liJB0-05&hogZKg+Xs?;hJQNyll}?y<7M#O)~DfH$wX5(`eaH^EO0lB`rx7b z{VS&)pRu~=&O8*8s?%K$uRbq)B+-0zqMLi`2(AE96XgSE`@VzPzdn91{>)N%YVP6m z-1%xr3+-R0Q|l2;Z}Z@1j+`3v{{S0!Uc*_kcG#@IaKL8p0EP9)?e3MLM_{BjM;WhhOSvMqonQxPUR&C)d~@)Po}F;gqGClnFc|M#Mw#M3 znqph-Eb?%~^{=3(TiVB%@#ja_zEijG#pB)T7O?tvuS-o`EwzYaAS+0vHxrIWYTUoUOFZ9jo}|8Za4n`wHe{RLtjZa zNmNM_D@5uU7$3X{;~#~5f$-~FT~9-bToq`*Rt?zWrD*uu#U44a(IUCO{{VRzNcX2sqK1slwI@G%C)1KLo;V~N`qXj(hCaMxSH>R+zu=)( z8nyJgN5l^fP2ufo-a{Po>HDUD5O7OI-#Yr>ZsNYT@aKy(uN7%<>RLXbZK>(g45h`p z?nCXK$JpSC?(;muQb$#jX*k=Anp=51$6$E?aqUJ#j#+@@brj`a?t(pWK+gBTq@NFK z*x=)+{{V8R7D7yI$x)v}S{?>nz8lwg#~r`itc8W1LdDA90f9jsOVGMT1{vA0^Jmh6 zs==7<+Bc`DC%e3Vo76!PCwU3^f* zXKt}Vff0HEP|11ez@&K#pv6VO9JQy2+5RGHS}c+&^6c$yVvP0J{$jIzHz*&4YU(zy zYIZkTee5f7YjYDtEN%B)7!XI|39d86unjZEdOo&;Yfo<0GqV2x602_j{tV=OE2&$v zDv~*MPbw*1G#WbZGOc$k~fLH>GQQNbn|^@h8JirRqiE3c_n!>v9(2(qZ>xjGp7C zp&18*UpV-?#l9%`H*~sxjjg}5G?GMiz9P1d5X?I)pYzTALE!c#xp8@a)|a)Qz3!{^ zU*-B9juRd1pR=m;=>GuB`eFQOYAuN}A;-ON8rQ`AIp>xyHaxFlYs%yCmW|>o4>H>G zh8e<1URC4c2Ac%(TU^SAY2{BR@voDdWf^iyMtwy-R~~4O`0w%J4Hr+niV2iSCRJOo z{{R#1Uj_KnS-RI=TiLhyc_uYu$vw&UHR&4Gi+SSz01%K2w=KIHn3f<_--aIxf8k_& zZqa-&u(RoQGX1AfU@{g6zIh4s&I0{dSE+@=^GQZKo?b4yRV3E|A+w!kG_{!maEclq7*I54m$Z1*3)}H1J zSYV*=39Tz^F6@E9tb1uok%c6Bb*tua8g4&$ke~s{C!nk^W2r_?)SG{dc3V&o~90sc}td*TX*Q2JcHshPvM;o&N-XydVRp! z8yIDFBM0BDe8=OhPWwmH#Hf-qD*1MFCm9%Ff;~G|)7~?>hg*_g?8$R%gBI?7Z?sB2 zX4{SefB?^Oc(0iLDfqrSZ9pyjD<#(b-cAb!AQCqYnB;fo>0UiI7g4BeeXUs6!(rmF z8aA)4kILr_;vGN@Mj>q)gpCH-Vb0y%a=x8UA6#O&y>C@bN6Oy{Lvgzev+l?-gY-3j zP}60K?%oLGQ*kHnO_WDFGBcJVfKEmMJv}QY#LI1OrTJ)*!#r#=9HT4_dmLjQje3xF zvPaBTPHD?id}b>0c1*mqfH|rGV}$%zSAy*LIRBt0*JpO#kv>h|p= z%(5diWmrDp)j%L;@ThGpq?+PrNNF8NkTZWDT%XA1wq3lN#w;?pWgzzlwNMi>Y7cT4 zsw(aTdvKz=6VUPJ4|?ZOrfT2W4K=Hx+*(Z$c!(c#kUyxd$miRE}5;SteQVFe& z2@-|*NC)^%4n4kxzDLqNBkT8G6u9urI-SS%IXlIkK|(t5+;iz#{t)q<{{Vx0No}cE zu~Nlia5+*tZXU;05LDWd1D2M6)|>uA)1I$sUuHDc!&XpgC`<-?p3r}@{_p8!sN7U@6l&;J0Up1v^f zpN_O&h*~P@dL`Oi+w_qS4-_KT6?_(`l7*K~#L)knFR0Iy50Kltj3{{Rg&Aj2cffd2sGRH>HE#Yc5> zz`PG?_8M|5Xp!V)s`Ee5~63!EC(R%7078#4dn-_;x2b zBBGMSYF2X#Sxi1+Vb>W`l_2CA$=tmTTH?VqHNVqjiDrso#vt60=v4M1y!%4&UaR3~ zZfxd8)NJkC#CHNGgSX-_*w)FW!r@JK-k1*(;-h*1S&_j65ZGV5-@JEAu7@A&+mN6~byzN%q)) zc*zmuY|qMkqHsrkQ}wSvwbJeEwX4V)T)n~%kvRE}LFv}9FKkct$@3EdU{kaM{m10} zax3NQ#m1++eMTB-!`(c)z_xN+Y4`0WS!bPDm6YTXLjM5u>)SpF#r7ME__tvi>Nd*` zLjc(x{EybSp8{yAG`pnQ#0S_5bva{>-E&>HgXjLu@kQ0TlnW&JIXw!hhR@@;{&l7u z{`DE++H~4Jkhp)dcs~1SAL%|^13k;Sjz2S4pAr0RCCh2v7VyQKI-a>4K2yA-FsAH$ zg!L@EpH9cEdB2Z7FvY4`Tljy&lRT5fC~0rvMK6?P#!3=kH#V-v2w z&F`#a)O-cwO&TAXSY~UOkdCO!f_{LgHN7d{k({%K#9{mgy^e3~9Y4%QR#4G8ju>;F ze&_SAOZW-rcyGrVjnoQIr_2HDLjp2C5-Y~O1;W-^{+Ot6^Q4Lw+_N%&=qA32_;+N3 z`$p~+RcXsj6ApTlxlhpkhPvrC<#cjlES9I&IyR*Sp{B(=3=O=XJYXNWo=W})Bk78K z_X;vW_vTW3Lf;|2+R+Q z^k6!hq^!+Cu&f`EfQjaqgr5eXHTyui59tz6jKHIjka0O3Gq9rZNPPc|R!!sUFq(cj6D(=UMSL z#bog~@d@zliAcr6+cxXDfEZ=xC<71)-Mgvcy=k<~7s58Niwg@&d1N64%#o`~$NR;N zcr>w7qbW`gN3EImHSqK?6sgmwuPCcsJ8j=akH;?ucpJr9My047O3m#S;N@cHsXRBQ z9=&VrZ`ot^j@SGHqHBH&xVcN1QZ&4?y}gtOwB;nMr0)I_c91=Ham{<*$GNmEPrz4} zQ;6kp5!-Po4JdQb)SiSMc)+j8j~?7=OKD#1%gySTWDc@fJqnA$J{5%nh(=u)jy z8r!|Crk-b+QW$I%D5V!CC)M`!^*+}4!~0ul`X#O9r-t4*153H>qAG)oT-X*RlMmuCi_r`pCM zg4WprM;eZSRB#1!VX&~nUBh;8V{x*@B^I<_*Yu2^3j8?mw}JEz>`ep1`fib>71-96 zmdJ?X{jran`?gJZPwgM@YC8`LjYmaE7SaQ@NOxpF4@`I4?c0IVr_&^W2`2z`Cb-`g zd_nN#g{94<%&Dofqa)edfhOUORGx$JHF$_Zard+^!eT06>M28B>$&-jp=tM1c!qdh zcv1y&f?2}=4{y7kE3wr+9Nyl6FxB+u0PZTUA;%qt2iCfcYr%Hcn$`9Gm1!-lgUVm* z)3)OuJQ6^`{HrI#I=%LtrOR$D=7i)O$~P`Ll?R{%e>(FgDYm&!t)n_Ji*HlG{AuA0 zP7ALu?Qyhi#`Iz~=j-^Nz}GFL_&@EM$JlLwWl{u^Il$x${=d?h)XF~?A( z`q!gPRB_cF9xlBoNvNM?d_M54r-q<~VCAK(jWs$iKWS9G_aX za}($uEs`Zs<=n`yaG;kLDaihOs^?-U~f{M~8^~&FmyU-d=W+lRV?0w! zpW%x;B>w=%9gqA5ku2l3wwh^FZ&QMOewCfg5-{cP<*ocmZ|&l{RU9nwD}n4XIIdU3 z{u=PacJFU-0@y^VTg`wB$BuJ`1bsd0N)H%Et@x_fNws~>@?h+9z|BzcWt4h{i8ZTP zHm#k!w#m4j89e0PPv9#lq}Hg`5|Vl|&ps||6Zm6HGb~bHzJp^8wTv6_nb{b$j5GW@ zn1ha|JYZMAw({I+TG_dgjKyaLNlDIBADKsOy}vUVO! z*rFR-WI*GLCoJUP4DpgN^1q1mYby;!v|Sb-I6#5HnmiW)ScY}#0l_MrPD3|Z@-UK& zTT6HO9@Zu`Irng_5%zvjB(I*>y8C+`aR56+K!n&lD}p9 zLo*=cc}|E5pP+14uF{+uX!4cm)JSb7{)-BVU;b#PRm zDtIRXzHR-Dd|CEABIiW8n}69PXhu&=90OlU__5+mE=CW*UbqJzjeM0_Zk*gv^>pRW z6()R}@rvX7R_^8{P5p32dRLOm;Y*k;?WIWM2pi@geq7hn+FyW|#hT#^hhsO)bDk^I zelvV5)4VJ2eLR>FIRhso4CJ2m=u)idr4({iqNeW8m+oRd6!3ku%lxl!N`QLTGvVD$ zr@RbCK_fq%c3%{&-%_`+vxSG13W0z-u*RRf^k0sM`dLGf?iQd;u zit^o+W*_SlKkEi7sj=}4S7{;SA;4txZuRH7Mz)sLI|n2#2V@?X+^ZJccQ<_2 zGMZ+}4ITyiMriBduZvoKy99eJ?{=ij2M#lXpKuLs_H^Z;}omFnST%}nvJ zQ01t7oABHA)6unkJz?>6l-gzdU@KhM!eoj=?;dv{`feVW>0ayM4~SkH@#UJ_cz;>5 z)dxn7H^i&#(Y6>LsISTE{Z;K{D22C!#!Yn^KC!wer@r$cnR!{@a*`*wVON88C#~|&lTc7us@5nUlV*S@v3TC?AqiOcL^P|mn4~DLkT5V zo=-mJy{%<(HiPs>}4=x8J`U+%8E$zfmEQB+h zIabdd&319dx^=R|fCdYX_eZ5eb^(@_uxU_;;y?=a9gp=s^$hn6#PdljllO=js3mX# z9sdBGW=M~5f<}KDw`Dh(9y^Yekt2_o<0sRgsqClOFed}GA(cF3rAeu2atKg8)Fe*` zBR@LxkHlqv8t1g_Ys-o^SIT^>r>SH;0s3;M+*fsQq2nMQq3k}MwddNsn9((Tp$N9T zEYW9xj(K?fgMH!ey1lHvvb&={k;96n{y3Yr7mEWa9IT^q=lND{uV-VdY13KXTEly3 zI_#1O&^&T4LI^w>t6``MDW1+y&u&KT@7JG7xg~*L-azJ9*#7_#>0aW3gZ)o8nX~1O ziQloKEO#2e!(CcU0_2Y{==UsI)yeFHozeRaN7BAr@ot0hGsC)w(|lW}-D&Wa+Ac{F zTglH=k#Y~?&$WJ_+*`DzM1`=uyC43wLvi6-UlM6Iv0hs%*nP$l5B0|%bbETAOyapQ zcxrfv^G|;N0M_Sj8y8Z8w07)#8>Dz^OzH#bW;2a2Rx-4R~Kofh}|mDHKO-7YfW5YW$w09EP$R826-U`Gp zKT)5~zR2;7`gnW6de!uf0^3^6FF)*|HSmSB4|(8=El%St=SI!oGFo*^aSyoWR^L==qd4QHxF)ta9}W8 z2%aM$CNNZm$vl&mUQb-tALBh?Y~XA33MA32ZX~k|0|lJzRDGv{M&f?8Q^Al!V3)dE z`PW&7DQ>SWWZd@`4x5~kJ&5Ny&rAR-$DO9^&*^M7Q9>A4uV$>a(`|Zuwe@Fdd!bLO ztWOt-wTl;Erxuq82mU;Un|1L1%Tb1C^(|Xg){w8u7NL5^9OJxb6==18S$X@kiWMD$W^5Q4PBFBd}IKC>`_dR_nryRGYg$HK~HBTD0J!Xs7p?AG7ztS+oci@>rYA zm5Uy{{cGs$Cr_T%UOa?M@rc{h$;EB#T$v|uPF7!~B6BZcSGmIPd!;EMWk%i)d9-L1{S zLhZE+2Epg?tPL07!&%+E-Qszd56}_9=Dk=}jC8r>RG}&CkCt_<4oh#p8C>)@=CH2x z!wsh5Nm(3i9+>N2UU7Tl(sp`FKX+jh*H?$se)@m#|Q7()lh95WFNe0_KvP>Snfp2+>X(e_kqP zm5-sxVK`TeEq-h0dLE~$#j8%Y5P}4;4a?}?=M?=9&bGQq6_Oi_Wpbd22X$eA*QI6I z$M$qcRE!SwxRI+aGB*Li$4c|r{S$z~sX{#4qKh)et z7;XUifN}?7EA`j*YrBsB0N~z*a}msP8JS7+^PayMwCzD+c+T>Zs48%B$Bwx7{+0UW z`w;3URsEVgC30JNZ?uf(JuV~_-G-I!kIKA9%c)Vr)5O7AT-JYcf1&QwQAKy3f(3c+ z$D#+r4OE^!csU3Dn!a9;=gG4~K7w zhEl*d*jNI1JXf3DUl^RO;CafDYqIdg+*4SY0mc;my{av#ZRm5l6j4K~T)^rV<}3zt z)aJ0hB`Q~Flub~hkK^(^^Y0^VtL46?1^nGe|-D7RRO* zyN?rJi%*9h9MRMb+QgfrOrP~?rO&@Df%qEoiwGG$BHtD#%esU}03e4ThQOzXR+5o* zz38-k9q`w|_UsmaFDoI+WPcApe;!ZcUaR8I3|w9OJMli5U>RoA^qY%C34lwqZM1Xi z)A6ov;hKr;E!{xI(Tet6KGqGiU&^3@1i4=`Xd8F~+P$~q2Z2A~6tdT0wTU3pu3ct^G#@GxlOR9vERp{3uMn}g z-EZs<6!;Pe2hvvVn zc<^;(V&`OF<(Pjjt!exd@dl%;{9=<#v_jf{_H6HQ7&utb03iF2#Yf}sS*#7IE2NHkk4DaK z!`AX>9w@N77)63uJ-E*}{{X(L>K5`mF=Y%$Kv^bxjof|KJOS;`O7V-I4lVw(c2O`9 z44*0E<^+O1gCCW3o+;PlxYDc(0woqu$QT|$SK5E^;aY=#hbk|#`k_6f_QC`-D51v{@Jpd3-&f-@d1)%zU}^E#$#!4+UZw!#`sE2X1<4{3GyEcr#A7XT3AcEP{DV zgs?A;LfsR>@a?HoMB$9r$t}c~< z!NUsGXspj7qvxBHQOs)|25n(a+x45ETIU@%g6&|skjDyP_#Obvt>ld=IB?Q+FM; z)a*N|Ge)cVlyAzT3X-qNyvK-?y_N2MU+a2ovD~!sNb;Eu;_^1;B>I!qy|3WSi+ESU zr%;N;C)Dqx%yPKTmVjUZ^~p8nJ|Kxjn&p6ea1T>oU3?bNG?U>gS#CBu#Icmzc>9Aj z>`KsAJh-)3mXN4R4sl`1@oD)Fdm!x z{{Xd)g#=H0h`>bmx3SX{SDv%V8{% z&n$_UC65fM4oS%1{{WsUKM&|$e49*IbKe!#>HZuOTr{qmM$!PS{UgJ`&aE1B?^yd~ z6=Z6u-QAd4Z-fB2T*r(W?Jcyp^!Tt8DaT=3ap?})OXBPC_Eomo$yJR0`D3|skaBV&@p*UsOyXNe+vyS*|d z2kg*?m;K|657bq`U7}|F)_pss$Y=Ob;CV7K_7ESgVp^<-%DK-|)|bN|$?#+0@dtKv zyJMVx(-o(n*f~57bLn2kL~1sJVAM8n&5tr`-TyxepARx#5OCsQl~A{AckI{6Fws z+fkZTOXjv~S(&<|@iRps{Lr7qt80Eb9v=9Ed!^3)T1yh$!cH*Ccyamv06OxY+UHk` zMfha4meObK+Qrq(c*YEFv9bMF{&XZ4wx>b+AYM!2FA(2rmjuYMLR>L9!xrPOu+QUO zy{$y|HhQ+NYNknKSB5k}_n7qkanH4Q@9cvNwjT^Gf<#R7uN_879e$PSI){wm@Wq54 z8PnqXPN57&chB(ik)HWu&fWJ~HtSiCyn54VKu(NLg?&gQ3Pa&tZ<0 z=3rsW+h?zgnx_R}{xsL&)EeH((F-JK7FQ<+BaMI$(vl4%1=FD|^Gq6XjzLzy1bbyM zRJ6SoRuDl7Gv8g1kSABm9$fzbFQ#kLwEHVq^$YPGu{K^D(ppIF3gw$TAYs!b%Md*| zuVSRRRgvUUi=3|`f8h_08^b>nCR{XeT!^MrVT|rYJqK*(750taiNCkBbx2%>Wf)L$ zN%XJJUl7{dX!`btdhon53kzhE9F8GE54Ya^EA3x_*AJ^{wsO833!T{qj8~6}rmUuq zdk0b8P-nRO8Swi@e;3*S`G_o7R?qEgshe*ISn2Sok)@SM0CI6!ei<>?gpo%*bDE3B zLf^!SBctS7`?FuvLfNR-2 zORQVLr;9|!#RP=|rxoOSrnb?ujFtfBDsU@ac}bc3IHj=LZwEpfb2{sHhl?6k9eicbr)^pf(KXBi`q8mwMBPY_YKM5k^*?^1Y&QzuZj z(`^RpiI^e<8Os{dxYHKS_Sa5``Hvcn`0jiDwbOeej>q1A@J#rK_+{}PGsFG15&r;^ z=Dv@T6}Lz87zP8WJ!`-};GNb#W%zmVDM-M3$ce${{yoim<(`)Mo%Ow}Yn{goNjxud ze+rx5P}u7HAE)^?t*FeSd*x!!P@}zSJe$r*dz;Gce# zo%Ilx2WlMm?~0`FxOXGcu1s>it&Y`~Gn^5V>%|}zR=^|-eQL5zwp@=~bf+wsIAT8@ z^+w@}vy6~)o;%VRziD~Ad2CKcan#gW&X)$Ur_E__zqxQTwXjf*LvHm4n#;DFu}1{w z)4gw@6F{xO82%xEKME6ZcSEvj%<~m_?j)Z}y=6^K(2d1L)twLBk$>54p3DfVS}v^0 z?-G*X8*2{39Gsu?(zSeT;n}q%iu%I?ShL(E82(e%c&)F&w8%-OY^FJO9A?-^@aSA@JZ zeXeSkQP}AEWDjw1I~*i&D9bVb06d%y^^xHPXdz=aGD|BqMFX_Tt^Lx{cbm`k>tmNJsn$#(F5vb`vkDnBvtcZ{1tIiGN!h)$vfm z&~u*eWO@DP$NvC`pBla(-0FTAyVSft4EKiO!pl$n+<_D2gvjHWHmN6J`9Wvnl55-< zJVEg?+}Ze{t>)JB_@ir^+hPPRyOo$eI9URH?Y}QQ1x4Ur2x)(_kHZVycUO&N@g>?D zJ4&z7v8y{lapYx$YF4wRo@w~&qS&SY;bPC-Q{2R#pB zJ8&zB_`deqZi#V>*j#?K z@z;p;Sai>WmS~s~tRYlqoMW2$r}o8|4}n_v+)3FQfDccdYv3Og_@+%`P11B|NpCUL zasJ5fifC(N>VMfkQMQ7@`$$8X*3t>(anP}57#~57Yu+_0kl`Wn*rMQWJsUosO8Lk3 zZ?tVI#~PGuSSsl;qbz+CnE@Y<74$Bp6p_ZyB&FkS5lj8wYTg?O?reNAV*daTw0xb| zow*~Q^=)4~e$o2!LGjPUa25cIz`XIF-6eek@WxLk;s%5W%Skx{C;pkfPHW_!+Pdq= z`0?YJGlLeQqyyafF`DDWyFnkOa0-jeYIAgl{@jjV;undmwCx_^-R2FbUPZb%mn0$r zGRNzH0QRV&@k+rRg~68w;^%T4^&VISkMj2Byideh(_UFke{mzte{#W2N8Mcfss~|? zD*NkZICR*_%iF{mfH@;L3J>M_*O2dfpVSyC)Z9Iszpv`Y)V3PbHxX?FNJq$V-1n~{ z{i8Jdckr&4HIxur+&%iEIz|%RW3?tKg zJ#h@Nf2DcYkep;34Wm8yuMxG7=zb%#xQogVT`-E{dWDi1IuCBR`q#XC5b-(izm5}6 zmQA)dS|rwYvJn*bUpvC;I8f)3gmee)o}3!{JI9_e@a>{C zwx@isNcq|fZu$QJzCp!&Rq=1a+HZ0WcMExo*_5ryu&b6$ac ztHT^Wy_91Z^)=-lGVvv}FCm12$GPOyEzD!F=N}p_8&mjsu2@6_Z8SK^;E)I;ejpn8 zU&Wp!#Az5V6eLZ8az0$=^}(-y@s_P7qa4xX?IV$j`R~O35Wc#5mPPXs0~IIl4l|5@ zTJ>%zX901HCuG*2Y~* zR~+sv-=L|yrx5`&ZIkH6GAaUk1CCGOT$;1?e``w)qNCOS z0PU@oE~G`ZXf!$YWd8sMutOS|Z?Fi#$J-|79`)IV_>ajr{1%MdyPUFC5902(!0 z%@^U`rFmg>EuGYD2uY!AGUinW2k1=$Tc0#R@E76|t{XuA0Li$2__}}mC{KtcBBMee zkGq?=fB3qr{{R$xVUv#%>Rf-*Z~nDLeku6JBmOFFOaA`=fAy+45v|x=e$T%VX92(A z9s#j}1>7H>->r`ed=U77rlj%Q=tWV8W&Z$6g!9~R^^(67ykU|502MB!*ZzBd^{RFF zo8t0w{{RUtrH}gU{{Ysh_Go<4G<-+!E5~|@lLm*lfwh0qp#=W`)plvcJVU zPZL9^+4yA0JmOgWy4_cAsT=gom;dd8o&;6UnA^XH%l}7YmEC z=o=%S%Uy5n;I#5z!4HYkix2SybT71+`k9ZdiJTYFgmjF|pDWR;>*<})hu&aer|sNt zdRZ*Gsi((MJ{X)Vz7AIuz4A_r1HMP;N)$J9Z5NoeMk{xnVU=DE#@M@PFZk7g4 zLmAIj3f86dA4o0$d3mnkO7HjwvMS&UygxU4>R9wBa%WW?HR&+O-pPlwb&YgW4g3c> zjJ3&)Nd5=X`1lD>RSx#|En0j`NF_emmUyj7A4ZbKk@8X@z%?Z%ep^le-XaljY0w5{ zbOdC67@7f5@?<82FqVv3Gbi>GD&rUv=O?jm6(OjS3N+o63%v!ng z&;*wcG}ukG+`%H0$Wv1rHn*fq7)piDh#32Q%jE4 z1IJnBfGNA~;gChh)NZbsXlK7L-CSkv#7**bbc;SXZi)6iL?G6?dN?4HSZh&_ zU&2yb14ARKQCy-BfGmG@y@k`C-Eime82xdTtml3uoNy;Ss@kcC5T5UWa^L3h= zOzpNsC9GX58c9jy8!m-5cd@@3Ssk~l|A1+$|K{@ND~LVOFkyn2{3pM6DMHgN(7HsR zu>mknx|LTp_>b;@WkpmY{(-i@1c#IR*>vyW65iapt-C>^E5i=}SG?NSz5ptqJK_|7 z?*`%TU`gal8u`jU139?gSHD+8zRZppBRcpvj}t zq?kt5?!QOW!iJ+>ld$kjhU^3OoZyh@?QLVMRe5$}D1o;d%*6|t17j?H0DV$RyRFz_ z%vtXVeV%@6owTH<$THaS$k8eL^rRM=J_vt8lUf3?>nKZwyb7`ew}XY!m6V=;vneqDZz1~j6`sWaf?@*iwUbHr)oIqwxP;=g;EzUo`*pT|TKE?o~!DXGpI6rK<^RZXR zI58Lq1klBC;plMq%T;`}K0AA;`0!CN4_2r5w;xusD5&Khh*<0X=j)UGc?qjE<`Q33 zAiP=WjAi9^?r^P91TqT-ig|$#rc3zRC7=MMyjeDIzaNp|%P~O<0Q;KAoqj1^3%F8C5G+aCgVMQL>~rP8_n?UP-Trn&W%xf(RGEb#{xQa}_bp3oGI{x& z6%%YpZ++V0L5u(WJ*;g>_FOP5S$>KB%14Zaf3g*Z0bZz7zH7|PFk}6a<$M|b*_>^R z+5A|O_Bn>&Wq1DYfM4oa@e9cZRB7kb<;rrkY zbOlwfU>xPDSBVn753^3(q{nWBp#eIi2!-rqyMHVWxuK1n9-P1GF;^a zrf`_D09xvE1|8RyW(*Z>56D<$@=dYk*ojHSP0}5Fu1(4xsF)*5O9lBAPY^|p&-UJ8 zAw9%z1g01whEC$h3{c-0+41qy($bDF9x?ceY#}@*;WaJhA^o=Ce`j{E_ zstWJ5`mTt^xCVATNI*)_oO}x>4w{MpKY&H#L8%^+3X%2O9+ASkU`OStsJ%y69byzU z5;!|Bf`c0&JNQ}Vc>!>Ah&N!Tg+_FKELqrUoB*RlC zz*|{|SH?vKi6fbn$X=}ofBG=z6C}l>LSEhn&#au4CS{Y`&ihq_V{WY(;9~H3u=Ssg z8^lHA#l*^`;uT<{v;Kk1|M$@!QtE6XLts@)aZ(hAgck%IRYL(BRXe|xJ7PH=PjF0i zolQmO6{88-Ch%L|CGBk*zismbIGJ1RKj5%f49uc6NNj~`y9EXYk6PSEZo;OKhdjVm z(XyChN5cs;7r=_tmlJEPwZA$P3;TQ9Y5XRmd zNu1$NA;K0zqU!2u%Ib79K;m?LnDCSLdZOatg|z&h{5Rcgocv9sxSS7IR_wrh95}r+ zSY=}PUcf)lHQ?othoj*8fFWeZ0XK1o1;Iggvoo>AMNjRNyZH|)4a!cWsKw5!H#Hz9 zrS7%uJ~I?9Hhw_ebz>$n;F=0)Bd%=NfDqay3McRXHG^j~cLqMuP-`P`yjtfv_boQ? zqURSYH{qqZI^@bPnWuoX9-$nzYyhN0;P?-)D98!KaS2ZcY`|hK^xs**Qn6wlCcAF% z3@HW~DWYCnAa%Wp$GjqvEZ?^I-O<1YzwZ@>gbROzrodZ-BqBdlS+=HrDv%E+o&d5T zj?{YsrrbxKXE=P12Kx#j6;KYo^am`dHhd2J-*;^~`){KZGp?+N9W{T~>6y&uf1hx= zm)SA=u!qXwLS>;9HfFT}sJs*$v{6B)^dw)nZB$&oR`>_9El)JSh2ekt<1fvCEdZ>I z8nQ;9```lXy>xX8n8E-u@yr(%e$H$$=Y1)Fx*Gmj>pDA+zP-$w&d8CmcWKHB+w>mD zoHam8CDL+*cbGTQ$HTDRt9H20_#c_)V3GeFMhCf)70hK#R2~G}AYgSS9dD>QEu9{5 zu8S-w;(@z%OEj~JtK0A1>fxsK7H$TDZ(8+Unn^_?vZx{u4`>o%9$mV?jySDgUGjmN z?Ein9i7CQQB3B$jY8v)GJ59f$!ptbCcQPOs81&m9C5{STowIdOE$~_1%#`S^9qL*|guISbjuRRZyD9v`U?uCBETx%uOAcO~V zD@af766uv1<5%d)_m0R3XND-;7d!&89`t_?tOEPs8VOu8GCTh}ev!*6$0&|wH{{T_ z=O2jj>JdgAd~b_Xqj`e=uDT69t@=6%_4pq_QiOO<0Q`%TqHMyN+K?K&vaa%FgKGmF$}`q04)%eEw~R91SATFicqVv zISuEz)a(@I$+Mj+U&^Nu(xC3&{7x4jfLwYsYLVMR)bVUN-aXA8g9?7iD?5EK3%3;g zOGhtXdGg}IdHs2O*zb*Xrb*?IgC94KZn_@004ARt2F7Pv<>U4?L^P_cFp`WfkO7Pa+htZvW zNS@QWXZ{o(#`m0E`r`eRE4|jO^EIA_C>kl{W;)M8JbZ;FvYv%;0x-v0Sd?_P26(QF zKc2bdCJ)2HErfrDKXuM@*wqt4q?GE4^F0-3b+y^Tt>bVi7b{zC>iw+BsV3lJv){Yh ztD4n_kFrEOnB@=}=$LH1Nm^?(3bWVXv1mBjZGkm5fK)we?69Ee`mo_5%W08koUon7 zjj2DA%Jx0YFtgCkrE1rxQ&-?d=~P4y3jTFc4KT5H!6dIGB)LGH3yL?zIpUxj4M4?= zaFc0UT*@b&f}B_MwAB*D`ueDiM}J&hORM{jxHq@-L&=20CB4I?&~ddfugQkwfoWmTX4ZN_BO_lg zh*V~B!Mrao6n+w9F@XMpujoi`_ z+Jl(PyWOR+F8@H{y|44(KYO5KsZtr4I*kFv$;`eHGGJ&rMis%MA@(AcQ4c;8V>j|X z{TLDgyB-Kz;UTDL*vUR{Ur=F&jjaF?*Al;@CQXFQ6K^o~jRmp@yrrJ! zOAh8#v?lE!xI}U`37*1n2P)-@-Wz&kHUYK#G&Ye6K)-=+UGEA`mrofV+>|Fs@dka!TCP0`tYjx}YrtQ`f>G)F zX}NO_*CZV!9e-7Jx4pKzCD`7_g)P}u0*GM((v(~y`gYXnn4iqm)$eC2H8W*^E5cFX z6Z=yCK%}s&KMi2)i)v0SZRLYjH*PziCIcwD zbGM^e`rf)e=3%#fR0SWouq!nHSCzG1cT*$}w=(?6U~v)=Ex51BH*s42Et`-f!;_SR zCGTbc;yS=*H3`QY^ysewTg*Zxa|>`n`!6M;eVeZ!zt6W@RAUO3n(rg(RA+;^Ci*YM z@L6xTH@91?i826wgf4tSKuDRA_x%cE5BdHLhA%qL4VDUgdxW|&Xu?4^_RL^v-vWK{ zKPv1{O*p_e%LQConC84IHca)Ec*;{Eb|#Qdx?r>OCC8QxAdj~l*kO|m&4&` zZF>2?TmOSUo;S8hU1|NM#0>f-4PO{&jpYK7$EW zMP|Aevi09o#sszWZD1i1q6e|y{{LVBfu77mO@SDkfx+Dm=65c2bq4C?1q+S2QZQi_ z>2JG8GhH07%>$6~rMyZ^Dwrlb`SGI8rER}py(Z1~t+`gdf1nQnQ4X+G7?vFK-<$=U zgkLh;B&hD&fv|Z%<X7A;Mzu75;&8|2Jd) zF8ji1fjhqd_4sG@{3Iaj_hbV{ia%QYd??25zPeo(L;*gTs@{bxXTrd&4`ULcG#iQ9 zqXm;CZI&M)8|BPA`TsLyi6N|~6Oh2T0i5$f*vhXqo(;%hMTT6 zU#h|8?o1_`rR`nsdn$V-Bw-n!4B>gUJiYM^2*G$l;dsMfRvF}f$ALgch`-V(#v_-( z;ofGR+KrR7;yF!s|NfOZ2RnC1HOjP;;PoqWe(u9F2Rt)0Z5TRhOIfCunw#yaMiuF@ zR&My6p_2Iyk@}>UBmY2~ljU+{G#HNqymJu^4)}DV#j>ME&pw8p<~<5TC^||brF5Mi zEM~uWXqr#g(5q57c2_V&C*oS%4a2Z`cCONEjpkzN*6_|U1#($MLzR~?dcRAlZ(MsE zMuJEau|j`%u_Io#zY#YzbzMkZYJiSiR>&}^9i-R5TisWl4oKW0Bed0TLAf-)mXP1w zcFFAa&w1z)M+8?O~p^fAv z?uholZg2M7z+zwf7l`+1&Z`;Ko{9dMp60-s-8@o^*OAsz8)zO8y_+kxkz~q`6qb%y zVPf-h`()eB>VNgu(>Pu8`!nyOUR?wfBhyg!b5oFv%QgU0s?J;`*U5jgR8O;4yX%Zw z`PV1v)$@*_wPgTGqj2Ekq}oZ0%}6+Bx|nM5V6qm!n7Dl4{q`tqn5<4)+)kAb?uqBT zG=pZhYq(k#oA#lDZnz?a#;No0JoaC`s~kHtBEn9l3BOt5Ej4hBtqo z6zw;d`s*)LxWlIkwaCdy$qGrnj=C_56^*@8^5A(h{}s@yVgKFEG#T<0yL?iLy!Mzy zWR!*=&G`lj&vnGJNw*1&!gjXAf6^e34x8y(bEG{COt5TE1acEQ{Z;uUl{h16#~gX7 z_ZYB_XJ}h-De?ASfA~qT@p}SZ&5#<5pTGBua`$#^3KQiRQ~838y*d* z-RozolUN7#X!q-vw<_YDEm99yo(JgF)F&tFKDFh#zc0+K65s0+bH_uqC^f!^ihJRxI`A``>-zOdj^CowQn9itEs_N3QpxsB15wdCsx+r_J^h=Eg zJEUi$Ys;>Ir{K~6y2P1n9PQ%P*_}l>E*@U3RvHX}2OUwy@0xvQX*MfFH=})k3VN_4 zQoVe@jE`QK-1TkJ`v>~&(#=zn`Qly~^lrW_N*+QwS0BciZ=d1q=I<$cF}CsgJ?D2) zDXbnxHE3^J3#le`8%y&VpOllvI&W9dNj}GG)a5Kwu+-f~P*yNbG_2=h5G|dU zqRx#$F|HRRWPcL0^Nv~zJEgR*iI|Rmig~{rIuGsS786@F;SVW3CFg z4E7r34Sx#+?3B?^b2H7APj^xM;Aba86308byTRPhsv!&EOHK7p2T#aBY`-}rffc3?%M%bjiA(NE+?v7G#}A!L_j-T4@O@C#ce_*Y-KLu| zM(uatAlP${isZgikDqdfMf7ug^lORWO0R_NH+3_MN~D82BmZ?_39w~te)#cQendO> zXiM#l5Lh5eOMp&h=;?eqsLXo(+bFv9e%{xgG-XJuhO?9vhSC4sLapEd((Ml%0%__DRr}PvJNK}k5-z}*G;sO@wva0AdPXQ86*bUf8S32 z9wK-6CL5#HC6vN4-7}Xy&Lk_y&{Fn?aikjxkG10&+bi}xa(wuy>QbY)v*uA@XHDwMF3b z3ymCPm=QSHFl%3D2UV%O-Ku4~%&#sNp5~l+J1q2*DM4bd&WtnpI0n!7Fc!(;TS;;E z5g2KW!0sK-!HKV~*4xjtBuGfB5RwdaN>LTG`7~wl4Sa5^0FqWgkuFR( zhxPUr&0yWd>~&H$99OhrAD(^I6-n;)xHmLq@in;BaT7@zJb974JhnRdE)30>JA&y!Zdv$U%!U8Mofc_{-b4qF{rXQsT!Otyqa5KML1l$H zQNd%khJSBFdzw~Hf^%fe&j{K#iQEq=9;V-cxXaM#PGsjod_T8W16#VA>Er896r zN4eVF0Cmsbh1Y*zDpW}lsN3nPJZ_?13|EI%)b|V6o}HBXy|dv}VUQ-zRbpo`-^&&$ zj6~F}sbg3ZX0Yi`$ou>B!{JWO;^=_ie+Aw^6&^GVuq#CVRy4^Z~#iD{*U zoUAD71iWP<7mGoXOZT|G%#ic>6E@7G53PDL$QD!M^d^iPA#=DZcmLxYUgJY3TIu6X zjg{@e@I_sDIMQ*Zo;Z%A_3$H(nS!+z6fK}v&(CGpK0pK(lY0&FX=?*TF3l8?xK#WX zActkuct#k|bF@m?i0z{7!(_fSK-c~W8Hr-8<;%bw7^l=NAY{_=-qN*}9ZAxx87x=x z&QhYvxO-{~#ZY{^Vx`eRQZd%p`y}6Q!-qi3k^pC_T>c#;0}fnifU~$qu(`zQ)Q`Gv z%~j-2qC*m#b5bEbjhXkZlt!=U1E+lN47y9nG6vS1-;4REKWgCR#lTjoHlQlH1n&H~Nxp0Y4tk9A>8UXB3` zJ^M)kwsAhGoB(@|FAKVrN28%)y5ugdbB&+RbdNe*>LN%nkPB99-q~#1fH0(Xvk=?4 zV8IvG3^VOK6xYe$_BD2jQUJ60=p`+DbaNON_6Pg@kUX#H16>q6xYB}Zz>CFZ{O-(bYqJ4Id z_j-{=UdDUR#b!pY){)BKn;3?o;rtYf#+Z|y=aoJEmVKC$qAL6Rs^j#%yzz-LP{)O* z?%LQP1!YF2+Vvrp0IK)2p?ZTU;-r}lyHCb`bHR;&;yA#~G5%3injhwGp0i$z)v$k{ zOfsH+z{<2IrOW3+&%hvdp!?b8oRpDNd@wjOxOn*bm2~?&j|29M6pqy-3kBkM6LvDt#Qs-zcUNB5Wsk-AHlFXCfAoBs zGz%|fe*F*2-{OI8^>ou#xF`7yO_tI9VGd%u-}hT-IJ($ksJ}{%Wev%N!RQfQxUb^~ z1CV9!gqZF(uM{vFe(P{qb?@=)efZ<3s3dS2mjCEodztu2kF`YXDm9I{<5Zwo7VoWg zwpGvLq?S(>rSn^=@4k0D8^HdXH9K_m4N=-2@MI=Cdv^HofhjT6lJm6lRnC(mkoAZ`sl7Rk z>SNtw+KK0nzhd&I&-IIS67AXdGG`@wwV}-`dacRxsck^-n4oLR2*!&Swk&RezY!pn zf?@J5Plnh$N;zDDZ;ZYEo;B&r=pUNK&SC`s2X@da#~p*1seH*?O z^=b+O0EqC+wE+FW)(X&jYj&m#gO9-zi_bFptXJk8s~ssrINOyT|DZV}P>bU*I~l9L z$_AfxOr&x%(?s%1xfc$2P0X*%P^h|cf?sAo6AvUE6KvloU`bv_-j#Y*i2rU9c3%U4 zhTLUvqp0;42FC56 zi|K*M9`!jhuyuHQkIq@06ltf$^+ZhPdMA1ziPfF=qx0}XGG zqe%px+?*VBgSj$uuUk-C?U@wuX3f#H7p&zrn=-YL0v~^>WCB%y@yb>-=G@uZW$XLN zPk<^(Xl?DF<`x>6xKaYLiU?h|<>C^*^1qno=W3g9wXTU1Pnlx>QXR3Y>~a~|C$rvm z+JZOAPx-3q5Td}GaZNA4AU;qQFMPkQlru-3GXCa5==%JU*tT>lPZ>i4N|imT?3#AV zuVK+cV(2}Tt2_UX+a=#Xi}tDVikfbu1zez$4e->Dk}Zv_?Wi%?a(lPZMwJ0OW;vG3 z-|$?UK*^*xhncZMN#4}=Q{D^|C$qYzptM|)w~(|oQ_Um4K1^gh{dQxukny+JURSVu zBhQ~n{U)J;-jg3w1;+*D{6t2_3!ln-bG13oA5-H;udK6`1?sIJ1?A-}6zFIe3)F{M z^RNEPKGiI8_t?vrGvOu8PrL~po~xVQXJtDlM6G$-t6m=^cCDb_u9i$m3+ew$ zQ{OQNXeb5kAh>htdS5cxG4JH0OjBzvlDn$qau&XGgP!EEd*XU6@RgZ2l`kQePCTp6 z)54rVdssIQz-%8P(V(RqG}=|qi?Jae=l?D~j z<6xZfoS}pu2<~(ommGG%_ob>euF+i-SCr)!2boHwd{?ndecu^8l>A3+gD=Qls_AR_ z?G8srAwzZX8y4kYc)oupmaJY<%43_h%WGGmtfSf^VZ=J&gl=kypKt9;s!xj1`{%tM z#RF-ZxwuGA(G5GT8Z4_-@~rhL-;^FoS;tUIj%(a|s_G?lTEIH#a@SG5g4}HH4pTm} z;6KoGN%O&T=Y>uiR-3rscaj7}ua^T@#Z_e&n^caPgrgkV@twhUe`m}}qBoQ|)X1J2 zT%ik9DaMn_622!x|Gu+}kIQNfrZZfStTe?M8235Pesd*h_`A&`^^rM547Htb1u46Dr>kxu&!k6{E2$DmhZLVD<(uQ!uw|Umc#l-=+ItZzELrr;vv9(71 z`|`CgmnhUnn8a&{Vr`yZmA5f7_eE6y*QagId({s0Lgr?<6A67^O$=wqpO;H2Y0`70T0whx zdWb^MX0xflxA|NC?++Do=E}dlC}y(^dC&CJo<``ddkQJb=hJfa!yM5?u}S@BW%RO# z6G9&KT>XdxduH9`-C?;5|BO}YZ0*DHFDL!uIL18}Fz4*&DEW(3XWU>QM?S~GT1nd3 zixs*Le0Qa|&on1Rcy6<+w|aQf+t&v4cHDa6&LqzZtGw?Zae~1|7QO(7N|-)P9aCva zNI2uB{U&;xYURdQjkqtmV!q+Ma??9t{;#%JefBQ^K8x+}3GD#-N!{GdJ<*xrXU{j) zIZu)n%zx489viV=uajfg`Y5|Kk1fe4Qr)SX%Az)Tg$4AkMExDq&Y~%M8+-Z2L@W`- zEhl>;)5A@uNdEf_h^M0zL+!FUc#=;+JKLqMD=wvuzxsV$nS7%R2Dv$x9+d~WCqu#~ zZk-qR7}L+Y*y?|rSNq}rQaXYZEH8FpkpJb^F9N2&yPgx8(dmH02rraowYR^^sSw+W z%JwcBENXc!zi29$ac%YeC89mx*1*JxWV2&7`0LTVGh-26Aje~#sywo9($)=DzZ*|Ii`?`d=g1pn9-#RBXH^@`wppSTq+^wM)J&p%!; zX+G-WxC=s4vvkA$t>IRR)#4o)D|+6I3B>7|LHALA3Ri7dXI^6wmW?-eAErEG!Hk@UwBbm? zDaSLWJ7G6vo^D%EwrJg6;G7%%-rriq#Uo^Q{oRS>%=FTQQoc3%2lcqY*t$tEPeXTt z3gSn{3G1P<)omZd+whke_dPNYgzb_kIo&mAUyrwtQMl>7FykywC*d={9#V08C%uMV zVIyCCZqFLqrgL7O3Jm*H!SK6AcBac)H44i2+$|>(b{)Rf$+C!*wH<2#6j`{Etr}tr zE#lPHX+5WQjsYOgk-L1zKRmn9Wlc;6O3t=kC!g=|)h%4*0~idr^1=@W3Y0*ei~(s; zHIA%Z@@gP`#&&Bhm@6x(!?&I4$0(3Jb2QWQ%)FyBaF{y>2fUP#9#Rto74Ppo%?EzC z(#*9?tBYA_+`^|#a5lS{AH7QZ#V7`gG3cPRKkts$lV;XyF1()tCphFR1+ z13FgwFS4rKhYC5n)+>=zfery9h@8{kO|ZdP1+RS{eb4`z2<@;AIXCcIk<1ljoll55 zI(DiT7PGGTBra3C*+vg^XMIuZ8DsyoTId2ucrlvQ4dgL+Q>y9L@AiC#R1IR!t)fM7ibqyKv%B2VPZpJ$Z+6M# zRc+9}R0wRdrKJ0P-HzGOwX5yv=$@@!qx!M?=&QFB!g%jebgBZyVC(3X`Gc{*M!uP+ zx2s{}8J_0lE8ky6APg!Q#jYHOU+}qzIcF!oD8`v(25<6GDO)rr!UR=UfUK*;S+vW@ z<^^qi)n9l`om7Qn68oXb38_etGJEpyFXH{hvS{F_Os@>FBO{;mfwz|g5t#=YB4-?R z-R|&j?iMMYfes^5x6z8@`^cKunFvjR#23(fn|D4p7;MBDuOGU3#sDPy)JRumE|j_C z=!uzvVsuwZdRK&#Iqsx(VjsFx@udBG6`A3^A>k-nO}<@tt~sx$nl-A&UW!o+C2~KW ziAm=b<6U_QF?5kS$v%%6W+MS!YLG6&BP+-m^K8pN>M0VdYi~zHJov$3w5Q)9a)*U; zToba^G(tWMtNGCgi$y$UeV@q=Fkx}Jxf$-R9BPU&uD43!zJw3r2g_HJ!3`VWlMbGU zuxY>F=HXFCYgpkr$;Z5 zz{X~NI!SZc@D_@H^_;#VxmD)JV4w;1UiVoOuB-_z>MJY*@wqC8c;6?Co~JJmvTY~X zCcTg{_U{uneC)oh!NtUwLBp1&|3KkhNW5B$)ambWFJ#2F;Y)QgDH%3>w15fA_7hu6AN&kbzX&1LAI z*m+>ZkK%Jao{;*2f4J@#=eDJyZ`x*ldF2+c!HOMrILeG^a>pu%c|E$Mj~}*i<`8pp z`(yfiBcJu&-qCtvfkL{yDv)=jwvKQ~_c2MElm82~=%IOM#C-jip^@hOUQ|3y<=!sO zoEJfYIY1-XS4icsDe}&8!O8EfVStkMc=@lAE8Vx6>4m1AYO)YRSQ&f8ndN*It95Ar z>f>rUrmIxgB}}_0*As3^yiPM#Th68FaG7!VsZdJ;{!@lwdj~B*X?(u=Lw?4OUJXOV zL7D^)M#g%L+3$beXFzEN7=+_RyT|N}hv$DjGP|Sf=K}V@cc8vWqmIgd@venySAN=N z;mXE*{ z@Vq=>ig$V%X!u}*^-J9VQnCW=|O{@D4lnmSn`5Z%Xt+rv!@rKbUp;Oo>aB|RH_If_ zhMKT%{4iNQ3$N*;a<{Kge&ntDhU8*84O+aM`6VKK%_*JByzepP_;_xRVBwawnW}J| zl9HQ0p!&zKr7b1&N)_Z8YOGWG;>1!vR-DfY9@!GG+-yRb_TV?&+jeHhe(&4Q_GS{F zOFM2MBP7Vb8eTQ-d;TuJkG1*Lt_Ql99<$u8OO$!U92S*i&*IGy@CbkcW(P*p5+8H_ zk-N@Bt7G1MKjvbRZzd@u>SVl0#zSr361f74TE)V@lpZ{(e|bg`k*hr)@{XL9$kq(1 zMQ2u%HOl0#G)Ido_c_fPFmAYu4%M)(Mo47S5%+?&QqKb+hC_dyhl`NsFMF+8Na9ZIm!CZX^A-zsu!q9C zS~=MCwf(Kv4tCz2$E<>=wdh0&=R&l^PPgsbdDK5aa^FPUy`5v@Mk9X%ibPq^JG8y- z%blg1Wl#ED8`-97FH2^`aKY-Fy~Opi+zYDu+HO6VetgFQ5@v+<4J}6hG@l@HMdaeZB-nhmXtvlT7l)1uzkQo5}5H{Rub!W&x5f!uB5rR6r& zZHO82V|k7kSxC<~Q@~}w^Z-$G>{Ngp58w0k={%ZxTc?{;-c-M-KrPGGwu?0{;CIfU z&Z!20cw(rI)6Wmkh*W1^2euzZ@opS%kGU9_E|;vG>Qx@*p(CvU=QQ}mO*%>@{fLb0ySQ}?I$jEOTl^jRP~Ex8E@NOR`KL3#v3{vsQ{&TYG3MAgveC57#W#CXXR@5)<>{wEM{6GOS4>Pv--$D5tlsE z!CL17c0OX+iV`V}-J3@{=@%^T^*p|Tzz$a!LW0Qoi{XgWIk&If>9J`u-{Z!moERab z$5j77HI63=uO?Cr#~(L54owIfexqD!>J^wLJgu!CNfq!lj!fEtFH4R+PC_qIXH`;J zY+3hud=71hF+;N9%j09FxJlL741@et)sQ=DQ!O-ah*+F>t4GUEI zbJ~>@+rD9fumgS`_cIz&qYQs8r1?__win}#^X;-j!C!pkNLm*pXA0^qkB8YCDiB8y z63aCBZ`A+&MBNhQIk4+o-7BF_h%J--JtR3{9Q2cCTnZbt$ye&*d<&HGK_h?uBdkRx zx!TeG(@lnglX=rTm0@wl((lkl@n!926ppr9m(s;NsJUo+^G67=o0rZT7o1h0eF?<3 z@I1%Du)Ackeay`|Ct4KwQEePheergvQyI&75@Vm@IgAaK{A#WL!Js`VU6p0;FlnWR zh5FD1o>R1c$=OsA=il;TO30oO?M}*w zg4@wcmgj?^LxM&!11Ffg0?fwYPeZePdTwEJNA%`ymVW(f*X;&$aUhV&z#I;yWZj)Z z6Y1ZpWUSpKvJ8l(`ob!APQJ~W!pOUzM8&n$T z@kF`=QHzzazl|;3U*(s(j!j?XZ4Y zZO|?!QRR==#RtWDE5&55Tk^iLdp~Yoa4Znwcte6bnkr1?rONlQ@f+^tFp?HH_HPcZkCSBLT-bX9wa9l3y6Ed#lH!!<&g^z` znq|l~Nr~xzySw%3tGX5APR(0IThsl@?nYXr3 z&N6`;itfXeS)*ayLG&x4pIyB7Y;9B$QXU1s1mEuGTYrueUO45d3bStinRE<8E7tbL zV)*Pd>;HmhU7vi$kY-m5LZ_o!G|G&()scj|oSSPM`~mwt0R}y;5$WJaDQ7gZwOZSF zEdye+C2wfabE4L)AVtYu#2qY4-iHS_lZD0H)rl(9%xZZ#K68*FagzG3PbSm+yZ29hly^KCz z#onGUc<4R2U^xq-Dls81GxHDDt3E96amUkl&uvX&8l3s}ht#1HPyKW=?%&cR|I_|{ z)k~z-dpSsHop5zI_5T1%LA1VE8>(9%FZlC?{79_-0264IdUB))GU%Z~vu`7Tl1Squ zf=)Q+j+LjhOGIbvWhZyB+xTn8HrnQ_VS>Oc8*}DPceZ|*$LU^%J3!s`_}ilYvv?+;4)Dm@M+(WI3@0Y*T^3CB46YhBUK{nw%5zBJRcO$%Pq z{6VfLnhieMUC|ZFwg~crW7V7tdIRZReXCsR8vW*v;}zCz^^HqSytS3ho>gIpNCFLn z4WU>l`Vn0>#yctBP}J;hnUhbtw-*BDL-Ir9oZ$Zey}-v@kz60b8wR}b9o>zt>x8(q zc(8+lOQ2Kq-M1B=L#b}h-G~^^404gRq)_B~5;Og1c*Z>qS}_D02*F-IE-EP$fmrZvU)cO+RUa;f-TP*;1H^<1# zpBMG+20wAv{(xZoE+rygIS&;yoXEh?c2{F3ktKb?}g_B-mt3duFa_@DI|}W zKWKeE!^Hj!d0_qB{+`FkkacmlEC=R)FM9Kz*c(S0&&B)8yMXewhMMvtGj1E%f`SJ@ z!8Ox-VV>tp)AZFKEY8g=i-Gcz4oAKN0bM`*6WhXA*1TP-;}F}3te0;>#kUjsSBD8& zgx7QHl`r4ZlIefQ`vyM{-B`-Wr|5UOk}g9|vF(o|`=s*UgaVK?T0E z65XybjieFThZ+1Tsm4iO3g(rZZ)%Mz`JX`D-@$hQmIql-^kq2)xlKnU@Hiyo=DcU& z<(1Ztt1$5Xxb1JdZ2E4ZGQ+UaH-!`SjJeEdP;|OEvjyW~Tc!u&h zEgS=u=cQNir^H=9!`9Nh+wD{z!_IxH!8Md@j?j^#1@5>oLYFL^wr5o>q}pRL+s*cSh@+B4mHzJx2I74& zkU{?F9=P{^gV)0ANS4Ruh`<)&C|R;&M*GRn_gD}Qp%vv9C@$}`$khysJTC^^AGslR z=jbud_}8I)Kaq5OQp)Z_wi#}pPms46+^e&8JBC&K$I`p-HNE7I2Omq_ea}>q+XS3s z9(bxVLOTy!aa&WzhT4Q|2aIf=*gm~0%QX4r zyT6Z7)tThIzKz6ipO_*6_kiih@7ERU-X^h^Q}E^ej4?dZT*u|d9Ahl+*bj1R$#mzr z(`8t1H1d;Mm4HV(7m;Mh1$Z9aI|`Qcv9&n6-2Dvwl=VpU9|c+>DOE_tRGeo{qaTMg{v%-TIHE+y2LDo^e`QuEZe7Oj=}Y9@~~fUHuS6N;N> zG!?}IKCu0bmmds%BM(^@{{Tc9*qMt+P@RBs4$^a3Ke5t}_*NegbJNUR{{Y{ET_OO- zIP}4)GJAv(d4qW)1D=?sm62sFyDO8QaZ^r$NX%fJtOz6=enz6VwGcwFC=_(Lmx&#aGuSIR=&`Wf{QFY<8)j^Ik)i6RmDnWDPe20xLcZehW#Z}9aS{f8X6M?z75Jy8#-9+p zJ#r72Z)J+q=lHiVZhs7ZRr7d?%j-@(m+5orFcg1r&E2og$KC$`3pDGS9|dWm<=$(f z0+|?`l5jFfuCwgZnTrgtU_M_;o8jJ?ml_?4mRQG>F`oQaPWB6Et(6=fTH~cb$_i(p zTM(l+9;YjF4Z|*Wlb_)xvac;!K@JLW-@nqj`>Uv;IXiGhJ?oR#wP;r4BAwXl&TFDc zCAk#br1m)tUdDNnRZvR5%eeD_>-n1UzZGc`-Wi5TkQ^VEzIh+7>MP!)x`;qV0c-)D z{Q6g)__1MU6RyQ|$Z*Go6~S5-)gG-HkE%X*@i&02b$eqK{gT~AyS%ZtY^%<4tU7h* zay_fcUr3w5_qPz(>MJd~F#}A#jdsb$L%jKCKG;5$^zNgoX;!ZyYB$!F@~aXcnpIQz zWP4Z7Um7*NHs(1#%`9d>M+m^4LXKtcSMA(3Q_%91-ZoxW5wkXG_%<<~WV!k*mRvJ`4D=9~u52GmbesdB8k#Tvnap z8=nvAiE(bss2?)M7=@7!45V}*gXvzarg(}k7(}akAao0hYxc*TYtIo$kGz26@WC7$ zSFP;lhxe1ZK54jD_gd8Cz8&6O_)Eo_PO1?kg4S>(7Lo}8L-MiXt^qxLEA+#`SJB)> zx;70J>`~svM@+B+KtJF^KkzF2*6~k+XV9-+>|2BcVswn;<< z(Awbbp3`-<@^TxX$Fb>M)aog;(>&VLoE4fqhT+IYBOygq5|XRDWeDJo^?pWEA0s2_ zROCWP;~lzjU1tGJ*L;L-#zsN@l$Nm=IP38X$0r}YkfZBSIM8WeZKzy+5^Vt9dF0}ijKax_!bFId+!d| z5H{P!L_J4R*#z~@EA1I=ye<1Xd^-U7cH%Vxdx8r~aWi!%`^;G205j6QE%^ESL`AIJ zwWWkmo0&;JXXa^R&t?nqtADeSM{qhP~O+qaAFE!m2%oZeV`;1YY|(!CqQzW{WzWZrLur__GZiYAcX?=9ab&OT9}LNn0U zN^w!Nn=_m$b3bPkQSmp%UkfTNmYm5DTmbQy`FeW3D42pNrOT7J!%Z^Oh^mhJ8?RD9k;Iw(GX7CHQB zsZ)-yZsa&un&qn%V++Lo8hh^m+`irBOE#1d$vhwMuahmMk_*8e;u%QB4>|U)xikwX z=Z1YGvlv=8L{~inXZaKQ*Twq2fpcTxjYh}FX=byTl&oOnkVyQi)5FT?pE-}F*D60! zejMv9;*W;j7}aEuOC{c&1d={;x%L3Z^9HqKwhZ|ToDQ|+pR$jP^n34x+Bb$qpr>50 zNlV&DrC3MiGXgR&cs&8)y^3V=*!3J&T0Gk|qcWwo%7N?6QkvTY@tau4ZM zCAS$l9D3EFS*HI52^n3yPH^_57)W6(Bs&0)fqWx9t<~Z~hmb z!yCU1$9TGaqaDOrhM#othg7+XB^9|JD`cx4!HMl&n2XL&6)q?vsrifXN8ne5{1f5N z2tLuf6m7VhhwZCkC4OxghH>@qP#XPqX+g#5MQKcIdlsQs2V-1YvzH*PkkfOEJZ4xNt z9iWx``Om#@)t4-+diZ$rQ@Q7we})#~;>S+8)ZbLpbsM;rX%roi#I7Dqr=ZAOaguj- z0=GUj>GIF0GL`b9a6Gh8fETs}Y*@=-p*{ym*zRNliL#?D|6M!|5KFtZq}wD~++JMXwm~ z3=1Z!Z=!sJTy2 z___X}3Z2-?J&h0fxcv{zY=|-dpJU6cZI5TVWZGe%Y;W4Kv;| zvc?fhoum+W&;I~e=DV$9$8PTDlK#>j9lE*j-HSy(kcMo?y*$hg0X~3?{cG2MVLyQJ z__JTq^{=z}dIpNo-D(pUij6|`M(AP;e)MsiF~S}9UGOUSr$MuY=Xfpc=Mvl) zz%FA0kf8TD1D{&^Pxe-V&d=cPoo8VO*{yA-mN??hN{^I`p68ym2^vaPj)$!>o=;r& zsN@-|1aa?CI_EX2M=?#~%~zBWR^(E-s2t*`3T`UKh`;eWu|M?GRBWM%t2!zHtyzE9 zQ9vFS@ygUm@o!sh6&rDm4Q#-r6mB3I&bBKW4fq6);j8w;b71_cJNnjbmRq(ej7t&% z_G9Z@e~&|7LusZ4M;8+_%A>0yjN|A|-2E%G@}XjQ$^p2LE1A7$qK@lTaH;aNNaX$1 z8O{%Gf2DcYsaKcQP+oZ$N7IRYW2U^F2XH0 z!CL*hZ8Np>Z6O_Vm8a9?ODGn{eDS84kcqP~f%UP9rZxO5$J z^QPr*$EA4Co4t>(rAu>Tq&y3%*kA}V}UBh>&J=`-RWcgB+Mi}V8bsoI)-=MD( z{iHu;y(`5DVIPJp{5#s)wB+8|NF!_p}OL9rCw|>O8mPJ`XQaQ-3 zBVF)Ljd62}hz-xIWc;=0s+DN3b?9-r6fsh@MXEdp;Xi@&Jr`Kgth8-PdxLKPkLH!- zl1T;$Jw8;ou zv^{o{`c_WvGL((oy`(9_WPWk@r^b4xioPJv1DOt+W=xWerSZ-)v~u4;`gN~K_@&}I zuYrFLH0^fZL$beJVMo~CQ@xk%Q)h-E7;zk7PdH~ShF+$*FALbUx5Nv{qGJrs$L3$H zdv>QTzpUtOWqYR$R?$IaU7^)as0TPTbn3zu=8eg(hpSfV66JS3E%67&-G5#MriyD4 z<%vX{q=*1dP1#|Noli>L@GaJ_7lZX}NV}Q!S6Jr2hc22W;c{)~|*%1=KuMYPaZ?3#UX@*2O_sqENi#e-I<79_FohTI%~$@CK!8rTK?Y zb#oF#4tSF*p8dKWcwkBG z(+!RfUikV#E7)}{J}bL?gp_^OA2PRaN2sr_!`AkZv)vyjh@$CF$mi~2Q-TIbtgD3U z{Of-5Cfau%0pxeAo0Q7&!1`BF%3%K33!jBw4SksZ0O)~VDJo{Zv;D7Acf#+71JRrR z07MG;QDWx0&SWuCo+GIhDdIfP7a*Ks>Z>4DphXz;D#X`Ug|?j`>KQnH1UAKYM7 zzeY9c{{R_u-B-pwDYEdrnk0*39BCSPYr0U8ayMf~gvb z8G)%rDRV~hzgt;;sP-R(nsi8ojxphL&QEi*QOpEvA4C; zH1dfx^}zvy9G5VwsaKP*W(80VnLK@C;Y&e3gf#n5Hifl}Fmd;OQJjx&O6Gif;WpGX z*h0mXaY?1%8rQM1*fon|sdBt{7yOk*dW! zFSO1ZlI&W&`{AE~^nDW6*);egP%uj<{A+1fo+Waf4uuT9Jn>KFe4YOQ1q<-hui%2# z$cnL`B!P_A<*uEioBc^v>Ewzm=P0=(SL_G;6aoOA3c4F`zFTzqSLHsHc@#R7Njzbq zEsmWz>t2o%+*69~c-f2G3a3i`>@iuq^uKvH~TtmI^_os9ZsRpa!p zt4dI3J<7#ttbmHMuv1KQ$Sdsjp_3w~*@`yMBkF(H?SJChd_x|xFaC%%(s^vLs2~>Z zdR7PQcsBew_<%p@s{a7!gI!TT!>PdOR7>2eDq&eq%rV6x!g>NY=N^?apuq&3k(ynY z403Wu6zoXUR>)zDdVAHF7^&P;1D?66&5<6%_>g(4G2vqb@QceILEffL%TkiQh~mB_ z-z!Khfy0PdnEDQLUom_^(8b=h;F%qEr}ngHzz(v13jPBp+nV}=#Tpu3Nq2oC>=Hz= zeEo(=KhN~9pFDdTTlk0JnzDIuORYSJ3CUvZ$^QVylkgS!{O2j+RkVTX); zKQw(ic|NFg>suDq?X*>n6>+vKyASt?>5oCz732Oe_>1u~!ZVwlGgh|o93ZkHMSmG` z00-uXjO1ih$9Pxv zyVR%D7SF_*G}h9EJD829elvmFu6x(7X}bRa_WDPDO9-~^+B%%q$!q&O_>tXvY>&~A5Qhn zTAKEjrq0?GIcam$R`oo8;%~-_e+KDt&yy|22viNoJ*(!8d*knn{B?FMty(L4S75$t zI>L*dId=N>s~@y=)U*6U{=~6UEUhR)jBqiWoSwqEKZZZEl6ap+)h>KjsGTnEcvZB; zwQy1bjvI8TgOEVLUU*_iCyMC9LY!i!J=vBrRV3VL-pjGW>RRrV1e$z$@|?#eJhCZ5w?|XAwlK8ngI*bg(oA_bJn{*9{d2%{41y4HRp*xv^6)H zNsN)EB$e4zU@iip{DHCw$$S8y4Dr4Z@NMF0f$z7+1Z+xq$&E4uWTy%u@V zRpn^P7Ek)r^PB5(L-24825U>fy3x|sWpWCV5#w$*r+$4vCmHR zm4U|a5OR!Jv(SUaKP>)Yx+7`E%;2dPPHNku=tx%PUk+I`l6|TPq9)$zKe|es6+Liq zjt@>pO4;~V@uOGpEOY6$kXqhpzF~PS?qI<}-+Sf^2nW}YI@b;G?^l-3!gE-pg=K-h z(H43Ukd2Ud$J{*EOYrkj(ua?29{S29)3rAH1^hCCo>R90*Za79V~#R=X1wZgaGOZ% zsMO$_N8BF{{8w?}T`EtuY0~MlN6JGqfyoZ<$KY$%gSyo4Do2)D8P5>ew;5CK-kPg| zLE(1htjYrQ;-JVlDh_$(tjyE+c?do_(yZu&`VH6GqF^@2YZ^T#7R<_G58{{}#o;`W5KJmAU zE%d9jcAMngwO63822hM+c71Lhr0PqOJq`Z=0sJ`d-^2Ymq0y`o*kl=H#`z_0_L$_c zu216@xVmk>lXS}wkus>nXK&J*@fYIN$HMQ0dXI@lnLev~6kx$?5|Vk&2e-Mei~Mi# zKjJUMj|E=%r^H?lyYPeBkq|RnWiFz8;gMSo3irszAcNYJo#UaU3RCvH^&fqIt&chJ z)y|J`<1IlTx@0Wdv$ra(_4Kb<_!;pUDfa32GNatv{H(jO2<*euSHqf@iu^}s;wfLu zg=~xEqmm-b!|T?&9|8Ef{y!1Ndulw8Kt(`vo^z90`xnZMop@eW(EU0(<*V3lRUCo{ zUZTEx_<`b=mwC8Fie)4fMIfpVZLCsWg?uRQpt+fft8@^4E`s!D#4OQ+Qoej2Dz^i_*YHS{wwR3S0`*U>Hh$0aGiGs!vXF{ z>F-y3Cn%3lv@ACtG;JBiO+)cnmt66U#fz-IMdT?7c-sY6es=@tr{?y>dKCT^j|#e8 z(k=HmYY!gY_+s|QTG84~JVQD<#D^Kd$ye@pAI`r-AiRrL)2%PyAi;M8cM*Z;${2q- z{KwO^Ro0XHB6i<#$c|IhnMvBm^8IV{cj2p%@VCM){Fc(K@^R1H71@V+Sm4Z}uAft4 zNd12!P)M7Xfr_@^Yy=$V)}n4X1J=7y;WIK@f0Ue`tx&p)2d5-fyo-PU>F?gDPi|X2 zp0%nWm^V-j**V9heTVxuuHS?@F#iB<E>68`|m9&f7u0O&%2ql(>*l<>rgh@X0JVL_oX z00Ek54L(ZI<~zx)aLK)^vz?#6Wi($$2x#8Bwn9Sdh*?4;jByH_+zlrHH)@s zf~4^?w#Cn>%{yB7lWCx8=E7@RyO~BG7O*s|ymi2@OZaKwza4n`D|gYfKrOB!N#dUR z@JHrG#fESR#tINdGt#)*aMhldyESBd-Qur<>)~ZVHzwui;fTL`d3fkolEUn#BrAa;{g;%4<{%24E{CHa2@uwrx`RG*KjfR zbI^4pkMOUeKV|EKH^a%)=W<>UcXj0#{42xti^vl}njkRDm?6IL@BHi8KV^y5PYG)1 zr|#XM=iWd5wNFv~liLqUjmH%yYGVwF(K9j!=BrATZyjnG7ZkvzK?j<(qYUd7fA!Q< zOfYJFB}ewXkstHaPzQ?qYdQFztPY&R)Bd?7ap7;lf*n%UB|MtCE&WXmh+6E&rr zlP__ft}6pmc6~nD7DkX@x!eXefxD6Ja4Tn8kA9srV1~%)kLg)gfyAZB$UB$H7~w|I z$LC&Mbg@#LpDjLPE(kfN;3#t2Y?- z`M=I<&xMulkA9rmvQJ~{)2T;cVC9G#M@-j?c>Cj4m*ClebvIYCIF1`=xoI4n1q0NY zpW{c4r0_q7uCL}tFvg_r10Z|XmHZU&93CjuE&PAt+v{{@{pF3UvJ66}_>Zd*`By}y z=b}64(}g&>y>5Lw;Jrff^Fy_})$Ss;x}0u%WjI)eW%u_r&-`ex%j};fIPXHEkX%n`u^fqyVW? z#w+2?b$nZK9J+nv%<#x|x9-4VGt)TfUajy8#Bz8mP#Q(lg>3GR?%B@~IsQQZ06(oy zC6(@UdqpQ}Y5Jb~#A>*jA6MsHPw&{_nJc|Q6)kzqkSSRKrH z_O3}r?bz$7%NQf7@O02fVwUiHmk_E4kCj-dJz==B%$iYl0u1C_kUxfO9_Q3mFvaU4Ol5K!}@&U)N!QAW9Fab@zRj&R8;1kBdNrAG@&R93`FCOxZ=LP zlf!@8+BT8m-6?aa`7o6Om7Q8VFh8ixe2|G=)9}ONpzx1|zp=F|NiO1pBHBbhbx9{< z4?s!5_r-bm${yMqY$UXPX1b^3&!D_5IxBshhQgCDDV*&CoN?(`KNEaI z9kNKNfY>~qmCt-8@pJf!!&THJP>=SxSONSiu}Brbd|cOWHH&tePs2d)8GO=ksGQ}A z?b5z}RU9M9C1!nQ9)x9x_OW+Ms@UYUABf9ksibheNN#X)O?@r!OHq?t(IS^&RR?Pm z*q(W>g}xWrUHIc(np+ELZs1oXwFwlgOmqA>>MQIW0xQo6cwy2z)wE;+M{dkVT#9rP zg+$st9KlAu9l|Xpa6h*k_Se1>p4Ec9q!Etw`4QrqXzaB))+YeP&IeAl_s8u;@uy7I zVV>F>#!KLglSLvkZDHIHInU-R^P^eU9^&?OAgZ$*mLD^7`d77tQj?ULwa=K$WlEhI zRFtmLJ-^|njXbMWh2_U=XRT@cK=DYEPnARSf(AV+!E}9H?UXV}wSnN*Lwm1Dtl5-f z`{Z2h>yhd!X;8HJj#y)Psd9BWyQeZ-7h~R;bD~~D4Yl-^?zYz@j1v|4Uu$h(52!TO zZRC5`+26D7pAFB!?G7Lt_3RCA z{h_uiWpRShsU*HV3BVq>HSdBxDn(v{7{xzjQH-B6xmD8!nO6#NP&##{MTol45|vh- zqcj2aFYJc6_;2wC-bMca(FVF?WsDHVjt8xCpRzh<;lIQMJ>*gU0FVuI7U7T_=Q-e> zxT{+b_a|7xzD^3`01;9MR1Oa(fuC9x)V9ztPh(OAAn~3lh_7+v+Nw13M;7C^GB6vD zp!cl3OI5R;2@=-w8KsPk@QKw4@3)`AxIfwx#@dI2G@B`HEd|mzV9T%)y#P6GJAqz5 z;g1%4N%2(iH{0aXVN<U-CV zWQx;BS@lb$vxQX2BTPhY%Z_%bISYn)G@#n^$AIm4jUj|Dng@;VL{?JH4z>YHO zv>&P=KZq69_@>VP09*0KpQK$~&3FvyJn>3!7BF%PfsUkSY4!K76#b!Rka&|+)I7G0 z=81g0+~Id&27SV@KVM4oFf=0Tb3NLBj)$#^n}sbpKlmr>UZ1SxHijD;kO!r5{xtY> z{x90;G}hf2N!}_#r8avH8-sM?O_o7mNopsi}IJbh?eBz+v9GdT@ z<0Z*Za*X2DN+|M;EB0rwwAOyzbu9Nsc2A!neAl<=)+wjj-YjSqB)1~~V06V`TYN~e z)pgrV9?e!ux$<~93ZP_@U3LEel@5cbF_0m6nHSvF^r26h@Yx)=ij|sCtGoXIGxH0^ z8a#TR$DMZKWh{v{*!by@UqfiW2=vW&NQnWG)ud0GW1M7;xXvrgJ|_5LTYn#yvYses znc3Oq>5w?-UW4$n;>;IXd)QsNN2%L4mn!baC$S#Y!rjtuYaZ*1O{nj3{9m)?gP}WK zUEH0F0|FFcPA-`b`N%7K7A%AfGfbUI$44~p#) z%4vib(Sj7Q`H2I953d*_zXrIfL*H^oRXO{KGw$Dm-Xw$KZkyo^V4d2Xt+en@C_IK$ zL6U#kAzSe^?UJ_W)RBhAAXmkouz}T&j66eZ%p|ai%sT+Y1dzIbLiFSVpQU}E+kyGG zIOe@nWOo>-^;xcMbP49R3<}>^76^HD^T8slMTQ)VdU0ER z7Sk>Dd(W^=N~1{?*BtIKIDCGFu&$e@D;>BQMmUH$?0T-N;?r$2*~Fy2-0jX!C(^!Y z@xP8A#2*y&jT3QLKGMEs&`ImSK7{`Oje2Ak_wjswirPgo>37;pho=c5uJCjC5%|~3 z-Z%KGVc{7XH`X z9@3098YhwBFB9q|cG|=PMH?^*qj#{zPuI0)>0bzbHhg7i^^X*Ijz0%!5e%Ow**NK5 zP&^?nh{^U@p>hsGMB#@Skfi>AH4No7@$oG1ZCS0tXKSI=H3 z(lq@cANwazxVdp|l1C&e%pJ)Y8OAzu&2LUlS||7!RE-p`8=Ve=@ksb@S%OImLeV}k zjP5-M_x}Lv*RJ@_SGDn%gRMM4WIu5??%jK<4xozpYeCXHQQ}MJzTXUR+CwhocVFI+ zI#7H$gMd9)lj38T@HhicNPSg;^%k*v8Q>64z9QE(4OGM{-Xf z3Wwq~q_N#x87KQQ-bUz>FC|8BPq(KPTf_Od)Z~{K5vXu+oDe%#MXmTpQSr*@QE5=g zb07s`M=FgYGXSc&BPWAeK|3^woTJSbEss0!{{Vo}^Iy|p(5xQwRFo`gHyyk4joW|7 zuh72=_VX3Tr2h{*3>SpLt0 z9}0AV{@nin`Z??6JC$ZEG1I+$UHd-`zY4U0=+plI=;x;`h-aeFMHP^Ovb;=jqfhl; z{RmdAWcZ}xM4#%v`VgRNbB1R0pgG4{W=S-dpwN+D=H{nYs-uc}xS$J&`8{gNHBgQ~ zPhM)$HYg>Q(ANX;x8YnL7CaL+oVz2{t()ySZNqR9U@@?t?zs6+)E?E{MBG%Pkx8qo zF)28^qw>$g+5%{vHq?#HvA4WrYiZ$_VUVkGjqV5|@UK?zH;64fGj(-v+O6K3a=>{{ z47gvR2Ox7^ulrVf2AfiOe0Slv8Ly%NwM$5sCPf1tdV$n|!w%pE>}%yMZr}S}#Aa8C zh~=UrAHdg_R-Y`jK8FomN;W-n#a|lqdwAx1{Zd<)fh^F;CParFNX|NdYv#>+;$EGq z_?7OXR1k?vta0ORo*hjzE@{@S zd4F+#KGq-@!B)Wb{{Zz0-te{SSu{^Ni3$?K544f}bMM;~g+269LSZeGRt18$1p1H6 z*DK;b9Y?3^iU~GcOoc%s?kBH2=lYtvnAr9Ej~xF1Y-$YzEXFcO`MAyxVfcS4`e*h| z*6pB&S<_{?MVjHFmIP+zO`(Hh)QpZR;ZFeH7m68K%gB2ktK5=(eZA}1d^@e&X`UwV zq!uKLi7y&KvpEW}l271v{&c#I*GK4x=8mJ*pwsR?*I{ir&+k!KGxP2?sT8hZR~;ObW6L8nL7d>b9Tt)KoG6YJDI6Le`)4&`<}9d}dMq01G==KE6-> zic0377z3jA`qxqMkQ4DYS^0DRr2hcqC9Y!GcqQ0v>;UGx$$U)jhRD;jja8Q*4tTAI zK?D01yeLHnrtoxblcr8MG{4DZnV``n%pw^l0fRafm7T9 zojX@2D~wt_7*6w2x$0jS{5>Cuz8>oqPJx}_ILOZgTp!biQ0n{4$>*0rtVfdZk9Y0oORJooow@?F-9H0%u=z5Q0E3DP@ zsI`qIODR=Y<8*tvWKyLrN!=dgW~B~EZT)^k8Yk@c;7<{Fddd7Zsm}sSYYoEPT3l{< zBa4inA(>9CRn{*5;3z*W~{I&d18X6#gH0zv0Ncmj3P)@})5Y1cZV_ zVc7H7XCGR^_zFB%@k?9s<26YWH!@7#jA&S>e)1oejqYJy&>)x=HMG9?7&A-6ul^V`! zQ9)Ybyg{4GQKJAWc#GumTzlO^1%r7RRaT=s<-!mj@gOAtK?$-Ck z-x!}7Yxh^u&9WAlsv!RFV_TjSfLwT<-pUw&v(T)5W+brlnNc>Jb|k-F?)__lw+K0W z$*()w9rQhC;pLouAJXn7Sn+jsRv3ctRdb9UKN^GL9hKFWgQu{CTkRK@Ojlx(QXRwP zPzHLCKppexUDko1N8ry7$Ea$Vib&xy0VgaOfjob;{IgztHv&Wdsz;8V{$2~q$GL=gAJ$Go)(C$17tN#GP8)J8+UpYFB+ygeC0&QX8 zPI2fCJx^ZQsf1>IM)_t!w@G+Z1{vKPfb1aig<^_0JYQ%M4@>_G_W3(XD3gdDVGm zPnjcu@S~@N{v^jVjy}OSR3MF^ODOO{)SB#wE|BO|E!Wj`@dj>MC<9jm9%JbNA2g%aKT*R+i6Srle#HecbDdhHk^ zaOgUMIj?5{h}KYlFOlHp6fes-`ZLt#O{3VJwV!mV+3UCpv!!Y=>sn+N5W2Fk0ENK- z6p z;r{>-TirVqgyuPM{l??;I6sAV`lK;Os@%zhmdj9&%bX5}BOl7XUoxiSRa9M1yU6hi z*?Tw9pEmq3_~EMjG1PUbwJ!wf+UJLD9C=q7AXf5XBPvW>7F>57E9jeVj0fTugnzXB zH{pw&PfMK;hi2XjIohj*KBFIpHJ9+WLXX0F?beSXtdOAn%Qx}FPs{mcy`pl#bIof?QLMDlo{uN7ZplgXzTelW@Xy7KXT`EjJh}_AwqoAvhH>PC#(H$(zf(RXc#~Gt^!Kxh-q7AF znNgpC=5NVRGr-T(^Is`^Z}@R`E2Pp0ZWVzIeZ05pr`=i50o=u1_h@v1JJOG)fPa1Uzxv*6y6`bWa=4O>X1WHyT{ z2JBpy{-VAa(XD^9bxT+eD>SJY{{Vq7AJ)G|lF=;UjtJLmaVU*cb^u_1Dx`AF-I0W+ z?Z;|(N^wpqjL1sV4!9<*Vwma808-n7PC<&7%cR?bNLD_j{gM9wsNnuY9v*VZQUOyBdGMxV_tRfzfX?q!Zy(D4DEQ1Lk@Tc`s4Di zo5bOiB~rZgJI`Pmv?mKyoMQYyzL}@9sTR(f7%~Yn)>5M z67EEhTsomS<9I+%z7rpXeD+^fQpI1P^jOMiP-oFUvd6^fbsyRLONw?f$)Zmtl_L&H zC?Vp{`~krK0D#oKH2A-8kW8>hW7-bqbAUbltH6I^j~&6J_}5zSmZHkG9w3Q6&KsiL zMhQ{%Wh}o?E7Ct`&xZFtSK4h|g`>*8Y+u5|rVq7x)u9;T9A~p02E3gG%d1B3?8D=Y zQ(X9ssB2cCwFQRWOL*9^2+YH%KZScN{{XZet1Nnrrm3UPre9e|Qb-Bjt~)v~;gtIJ z=xfIQ4*Ybn_$_azXr3bQKBI285(sVe9WW%2O2pwo&I*!nFnvd@cYhN6Mc{9U*OJ1w z9w6|(wGbiI?Eqjp5Xs3SwsDHCNp#Ua$kpCbyH|hLP0yBoFZ@}PRq&(tt=wP0^FxOQFk5lQq4lo6;$OoHWz`Ip`t{bUYrklgdvOYr=m%5z zR~@fMYw-6^Nvg<9!2A+gw_+yv?A@;2iJ=8y(%2a3Hzb3UAM(c^oHU+ zHV$?lGEzUi*?$0kTI6hEU}90hX3yo#di1n`@|c%;t#&&<56;$iDUb)2*mXbMJ^ujD ztzOo&nJll8>f3S-9atO@`1@5zVc!tDh-IzDCI_KI{s)iBx_vh0JDU*$eDSc#KXpIh z{HvC2#$3qhrj(<~&#^ycF9t=U>e6c#cZ}(Ar$Hv*IF>mEaLekftTWi+zM8lv86cb* z`MdT~@pX;Glos&>wVFp;dF^)LVw^{X+0WdSRInYSS0BVH=?jt%A$JkTz^B)2 zHMsQo8oqY;>;U-J;{%hQwgLYDkdnTN@C=T8ZKQ%h%&bq-V^_}q03Apl8$4b}$opXb z0MThrp>f>jEC9e_rx@v)+Okf{O3$=#3!LYi3eb$48_Yi{#UFJ4?Ak6i4~?b=qddIg#iox=@YvICb?rY@NyMt~yg``fox4s4Zk6$0#y@}% z_|xNpT1M`+SI$f9EweevP=a z35o7)*iCU1V*)k|KJeCHn<@G4O`7Vd4!tO`aRe zTuU39sWThn2aMr|UKm!lj`ck=!*`K0UR|-ZEw(n0geA{AmpDBKQT!}@Wk6H!`}Yu} zLzJ!|AyOjUCDPp`UDDE{OF(J}2nYfL=^WkCDczj|M#IRFKKuUu&)f5IJLkIZ>yw8w z3<&N&lQQzGi);aL`5sTI0m%phWbM88QJ*u-WCXxP<8N=a&>_U)suJwQRB5kTx6aeC z;*l+e@QK_?y0{mVty3H*I4!bE^l#o zS;_w4r^(@5YU#OTdi4TfPtwYba0Lvn(rTbYm(@MHV)JLvknQ*t_ zX%y4UH{1Wq!x7zkY5FD*pdyN`>Db!t5ageupw7y`@^&7#h6Hr^!%V$S35L z&bd=vi9s8Eor9CuOll8YD=zcU%X3PUN_T&=Ro)N6Ea_dbtoXRjiNW*fV&Cjp(Bu+r zQ4b`hrA}@^wqVVf-2<$P>U{*hRIx3Chcm=txhs-NnG^kn5eJAo;FUKz`QV|~C-?_ZQP^7kFZV2t?Hl-~E6@8jE7$ErSO;6D5 z)QWZ`xoP-*%|WDY`P9WajaD!lYeHYMcRQ`*K!OEX6&mOL@vpo*obsuDWIyB2SW!@; zw$g=~F%tZR{a15+4**SKx8aiFY0RgAgs`ZHNK?)&)j3DW^WPDg8Hd{O@J>eZGI+S{eP z@V{~H48Y#?z8iTDvw}6k=?XpqaSY7?vRS}$007Vl@CN98PvC7Tywyz*d#rwtuXx}? zGPE#JDI4NP7dBQMIq6UhHGo8^!(XR@bJ;Tl@PD4_tK!Kn%OME#|#I zksYz9<ahU2;L(oC6WbJ>Ip?Y88k>#Qh-?LG|bV07o!HxCzqe z$t9{(v2bO)$wm9;0-TLWrsthJJ$Sb+72N;!5n_=6eG4Ui%=`y%7$t%^*X$cbCFg?X zR^8kR_#hnHULc(Np7yc46%SJw+Y>1xYs+>9L;;B4uR~$_VR;NiQ<412W_NpU(ffjU zSS4TagB4KX^?!ihNzI31wE*2O{VhasMZi~HE?>~TewREz_|8YVW|Yn!TDyN~4?@iD((cL|-it*^BNDzR#G4i>CDV|2Q@mKX@V_0u(Q zE|_&@X;HSKts|~W9@z-_itlvEGNGp?Xp2Z`5R?3XC_@!$vNcX$@r_5hzWexQm$8Z7 zw$n8*A3np%SOqP!)8vze(Zj*)7wi2kCZ}5HZ()_w(=@wayL5=1t*hgI$T7 zha&sJnX~?f6g$xCMq^Qfegm-LgJT*>&Tw@6e$lvnE_1WWkL!;EGQ3~gba{vdBcH>A zvnLb%IOE*x6)00If#zk$in)zx(T*4waz^f*OMeOrmBY4xQ5Z6OKtwKu8dLGzcLg7F z3@oNVHE!g5>jS&jH0S9RUS2!gV8*6nmBIWmo41DdG)WQt@wa1VJC0IJ43jfu7HA(H@k&F45O&BwjB|tvyEu*kB5u9NE2; zI|{O*`GpNHfzu~Ax#`wnL^|tzuGG{S1mlt2T2V?0Uv=(b1?cM{`QNPUc*31(z^zV*etLo&DS)_vj3LJt0)VMo_-Bs{x z9E#(Z6Rf*=_YO%KLA6!(OAdUfYT4Qdvdz+TlCM!t@K_B!K=_PI1XVcAq(AyL<#PR4 zLGVHR?2Tmm`hQPi>DZU-z~5$B51L5nl|X7gBKh9PD}7Fgslp;5$-x$D_bn<7jd4?% zi~*$bqm@nN)-iTx@SThyO!62-=}0H4`h!9&+ZKr!NsqJfYGY9YF|{V{C`lK?3(H$h z{1(dlUU5qQ#NSsX)3L6V(#YD;&6QyM&H03N_Dy}#5uQ)9F0SQe_ zzUY#N_|of2ZI>2r$LzP6l^U(Aj1xq($P&WhaCgIgMoIeL>NnEXOFYZFDNmmSalHi9 z%ET5sB2jnvj##sNed34X!zNVL$-@TH5ts#ACw#-(s?`9zC3U>~{rP zmc36!pJesNr=(_6d)%2;4{0THJ$4n=Q3G~WRu!Vce*o+7gs5!sv84-Risqu6Cj7A6|c0a9J!U%+=f{@!KYhqb3K z+_LSzB{|))*zcj@0v>EyQxEp~&;d@zz4z2{wX|hnpfO|qBNltjY`_)jAS--$U3}0& zP?=j0X&niQSd#zVFP2rbM-g|gpY~JR4Tj5Bxv86Cy6StQ^xRJl4^qFHx4Ev`($<5}%p7I2(C3 z*FhLZQS-DHb!@Am>Dum+!FJ^5F-l5bJ-UsU`?8IjzDHizP1p!|wiYO6mXzyg40HFG z4ZOFWJ9r6=I?l0snq(sU&?w$i4#h(D=%IRboUZ;5ZZEAbD=0PaRQ|zzf0FM-dg=A$ z@D*lDMZ(Ke1_Q+s&TROB4jr&QRxb6gKfC|EzEsWPiX1I7?SME@Zsqy#mRyFXR}yK} z9Fu}!P*<5s>O5Y^`!a5=I3eLRv~j=l)5XKB{wTynH_)-p!lu-COLY0=qQ5;h468*@ z*R}JU0Qlkw0E*ISO@b*!3Y)6`x$jqbl-g=Lc$G!8I%+yF#cENlsaCmM*a1DaV}-eb z^)2y+ovAmAA}=k|fUPt91WN4RqDEWYVlajw8Wi~1_2yBm%|MMlj+(Nc zyJd<%2Om*m5u~rL7C84%Tkn{|W{v8*Xf13`sbns^jDBkok zG(9;RVkh^-;TR}kN!DY?vW&OcTj-9-3(mTwjhCSI{>zsWBB%5IfPJYUYN+8heF0>q zO%+(4ZJByuAapvjvF$^#5woP)Vz|b$B1iTL16?rDPth3_abnZQgaz=!3DTtD^}cAWPQAj=#G+;}q( zcUdqXVKM%AHhUpC(Cmij=tmdll1FiPBIL9q%B(zJ)QF}Uoz3h&dD1$jS3^FJiTGU@ zHza)Lz1_`OrJh?HgfnH#L~5_cdGkl%e|_iv>~1ciF2W#88sn-EGeg23pK#SdYxhH| z9Dsh7-#G!?U#O^*Bt>y7g;(6g*YM=|vW{E>$iu4fI7gE();2HzBzZGcPFU;2;$L{n z&+a1=A>1t>@}B9ECE*jXX%%!(%>1g7daJRgdTBl$Yf*Eu{I!fb*%rOT)r32Sus;n z=gf6iBCyGO`0$7tyh!aX$ctayPwZ5g_@kCPc^QBAh*H#5g2CK#tz5JZ*3~T&&+Hpz zJUN)O!$Pb#-qK19vS3keoMS_UwHv-&|G2ANX;Uu#eB+&#T0Q(iD^iikmU6rpzHi3! z@Cg~m_v@BZOXr(htKR2mOzCNsncxUta4y2{QO{{raaW0l_*2S~$9Hv8-b7S5t0eJ? zBZH(UR%n%VavbE0bY7kC)Z1ORkD2T@)lFZCLKKDj`*+vPe35%jq~m`Qr_$vA=% zwtljaO?N57`Gi28(sZJ~opvRR9XZg7U^_~yR|nn*NQ${?n>RrW@}}p;%}5?4rpC+s zE#!Lhzmt0FLJz7v=z;7TN*C}YPU~?_x!X;F)y@GFwEGlEYI5R)_AaDW z%-^v1@q}!dsf+iplupFL1Zk=`>*%-@hZrf)DI_kFLa-QFO0EjipY?MmbeFvBS55t7 z?R;5GCsh)znxRs?;-;ar{!Wfi1bwOgBM)W4V&XdKm3}AY>RGL#(@Mr!8+ui+^CYh2Cv#klmF9Zb6EzcruTvO2)rZSy|i|C}Th;}V>S zNfA(KGF(5yfV{w*fu@{DGsHgtxb8HvonTf>zO?adUl( z+DrZ$Tlyg3W6g)>bIUNIPG@!v1c{qzLsgoj!#C(qIA3fPkt_ghJ;ZMwo^ULDuWRyP z-c~nt#7X#T^PZe{z?tzR$q>7Hh?T~gRY)F*bq}KE~(>p(Tt~~!s*QvHwCX;iY4TfGeehTep zzn0XSJgPqy@hAAO#6B!Mk^fyKG_mVQ8XDd4nQM{ZuzSMfFz7{$v%G?ab<^~F>+D7U zy1;Ge{hO$!{XVT^aP`7fv85INkhTXZNR}-AB``$|wpccvIwGaGq2G)=l~GQ8m*1F6 z3Rm4sw@YV;Ax|}=VUUY4%t`@>zhs5S^iXjzA?6Ae$Qru`N8abmYQULdU)@TP2KW z{ni>xe&cu$XsyZ-75dT}Jq~x#e*~7SIrZiZgtj38pIaJVuVEqw{MJgNGzRloF%1CA zArHnCZKW{9!nUlbb1r(Xt4{2ovG09yvPkd4znxJZnFp&mWv5ns!(e1+u;Gjj8MJL> zY*bT?&C$|frK;J5ni*rm;jxiNaI#FaNcB&<+?O`4WaUg^$w zljwmY7)9SnjM`M*(!HO`r4~24C}J*fg4X1c^elfg5~ z=-1GVfn%8sF0erLyZBPh$Qn5_xfw&NCag!W8~u$|U?M59S)WuQe zXFl6xgYImV4)`naRQvE_e6SM`NEB;|bEa2RCQzSuknuxL)Qfm`2)Dskk!XY){54Uw z^PUSvG2Xjs?)DGB;epCWO{#LvlpDmNI5dV(7;0}tR-rJ@aXQi9QX{zYrzG5sBpj%S zaczqvt^kZfnJ%2hZ|*AxHchslo{q=2kTG$#Uj6cafYu1X=DlJbN1nOJ-?nt#r&<#G z{Le3I_@p8f5(#$#PTVeOB}FD0r?}vq(|fFO_k#>4BkXFUg*@p*KD*={o?zEn<2Y{jLha4?goZ>gdy&B-m_<2hE3iS313 zA^3MB-kqssPSj}{W9OPCR(d}fLM_^Ce)wNis`u(8)>JbA{9tpDbtJUus6o`*fh+3* z-AP5qFu#W4&hjl{z=!4Rv?1ot1AP&aA9U)IR6@UdUu2vuv@tTDtBSJwI%dxOC>m~_ z)}lF-Uaxsdw3cA%cFoq z^zxhhXk)2thm6oM@S^sP`Y(JU%LiJWP zeF;+qFQ3G%id@QkvuUR-EH5v%7|~$$BD%Te+iqe&aLpIF!L#y>glVFLx;ja)#GT8j$b-Xwg-ZOL4@hR z^g~1Mqw0#K-z55v8v{YUjO#*->-_4*Ge-gH&iU&K`;J@UJktEF@0X6GhN0rRXx6W98TYJLN*&U)(;4&O1))ORy|5KF%PK$c_71|+KpQtkle0B zyUBD=XNrK5-veuFDbpcPPX5{JwQ;I`vA%Lrci5JNk6??+&SU%m7uC zY-{5e%l(IjTC11R#Zu~HH265&tHzY$m9mDT{8p`rzQvt~dT&hf?{uU*q|@ovKC^27 zfUTuBVusLjp9iuDs5xwEIFOs#hh9RDa$UE{DO^8E$BzFK!S>9cvz0dJYTQ!Yf+H!011Dc{@j$T zn59C#R(brOxnG<%nRa9LTD_Qhqy}&D1UM|YzW#Z8)W|xi1p3dur;^P>lcP$_-2KE( z9V%z^4%OWmPS1F}SI)M!i7_4OZHg=l z`13pe0LRZ^#VA+5vS!8#=JYYu$M}wRADdqYu|NPc>srw=jYZZwkcn+*6C(Lr$W4HL zrodvhJ48I~!A)O+EPxz=)iS$cEx*?NkRr+?dm2i7V1K0B}KYX-_`5uH^0 z2nj0p*P#=gvY36%oJTpZ=72!ipiSjIY+NkG;AUPW3zU~?>&3heP~ST2AYOCvI^R@# zNqS!@SyE|)!23_T;zd+IYIS~bSt=-EsNpelH(!q7Z@7$H4xR3(0H*0cefWlMoZd7w~6Pjfo_cJ z4NkqVG5nmgh_XdJhQ5Q>Y%xWT>8_?8w2&q?2t17$zWcAwbT!UKL1jn88ZOnisd);H7E00}Uy`BC3| zgYnppg7-50sIGt3XGt1`+E%qTwuhiJ%EtD3vhY)TH;+fOG7J5 z(aliGn*o?H1pkS??+o7Oop$Fq>|_7swyCkE-g6}#j;1!?Hsyz6x_NOXlOr2+IY0D`yan^WGPMj@%Ch;|=vvYNW zGrsRzzn54ZG55>;K!B6WoHuw-(PiV?Lna%vP-+}L*B*!n?j|l6ImX6jbiMk#II!i| zF7$OwFe0T+jBIU6aYTL$lu|>qL{ThuIiPK#8X51_z*SxLv3XcXk`;bY8Sy|u23kq+ z2v6w;-T9$hH=iZacJlpS3m|fP-Uz_KS9xWgZ!MPmeq8>%C9byA$%N;^8yoBWS-MVN zG=y&vhy-j}HOoo-9K^bWax`MD$uVQ%Y~b#TN%~&*ZS;A092ixFPI*NL9qFMz;@_jnr3;CcPVTSlJuy3HCwT~B8xqF1D=Z4P^M zg8JxX=&f{%q(^c}N_)4_(p^h3HY_0ODD-;iT^=j2yq{B-k8emO7fZW+jRK~kBx{+R z6IgEup1h)KxZMrF5fUy`b@%9k6%QB{iH{dwk(R!W=w0p_r?`PucG$_SpC!vnKvCNa z3SHoBX%bKHyJx(1a$d)()1HT;(E7i+{5EJ4EwM4ui}9P9_uMuQ*}N0aCc zKY*ZmTRvZ;I3%j6N)f@-<#xkAeDN({!A#F~U|+s>78rAE9scIb`P$@sMV%fjG~;6{ z1PJ{6>>#tk64}weMAWlN=xo>PS6>-lD0@@+4)WRRahBGwV^Kpjpbr6k!o}N!U@`Zn zZz#O#Giv(#*lsdpfpbMmW!8hfGT#Lu4q^qBp@__H)Vc_@YKan0cSe0t%h2Ff8mk@I zYxKj6=N^Y?~F{ro*iyA4)M?2~QR*4V!Wa6~NIYaS4(cQ@dV`n>kWApG){ zSl?`xu1B%Cm4)YpH@wyR(ec{nT5Mvv=O3Wfr)Q86$U0^D1EK}L@xR$i*`(ZyvZ&a(k)<98#xCe<+%b3z3I${oe15)^?#pcGm-+{ zKSHkZ&|a80yyh#@5TYN>+74til;k$kF$THd=}OZ$V15CRo(VpXO!vpK#E9{34BOrE zE$hv^`vJUl7W^CX$f)uU(0MT3%3Ys$W;21iKr5;%OalA?CNTN6>#iz8V!VAxcU2v& zcKF1sf|YdMEQFgE_h`RwQ{wPeY+qs&>)|}MAwf$!z3Qn-!!ebEG|+SGP3ss6TPcvGLF~Nbab8n zOR*x~d~6z3XlU;zCZSs2QbiX|`QVo^{<3Z~O*G2f4>#R*pqgKiN%z;va#aiOsyvB6 zVubg0=#3Pde@X@r=h?*qsc<_xoNFhauHaX<_-?6X z>W1h{@`A3S?zK>6;C45eB=APg?oomVV!XG4yi>qkG1#5CZTaUV5}Q}S-|c~M1#wjw ztcYwxnU~P)m#${h(gFk7Woc9L$a`>bp9|AQ@~C^5667G?9BS|=x;3YR4Ofyz0u{wF zE>CgyFZSBW+N%^0LY$oCU5adKcyF-8z7x&WYB|j>%CWbK&0iOutv|3xP_}|J0z1@y z9K2`yZfG4x%=Sph6Vz16yGaxsmtoT8KTMFb`=_3-_<@@s<*8w7!DK`%);Myscj~2r z9W99+GO*v>50u)tagB6?y>@kKzww=$*DlaGM|73K*{Fnx0Ro4~1C!T1Z1QG|ybXs$5cU@u$5^s7eTms{bA?vgQ`#RlY=!x{jg zyO!r^zV=fFm)pE1^XaIOCNvHP_RG}Ic6@hD$2-Ht9IdgEpX6+DBjb$k=grtI6^yrOHcl70*CVN^tMQsj_)V~x?zUn(+vsjn*Ai9LF>GcGAj=3!mKe*iNNxt{_ z^1bBy>XP(cFiiS#8(zftNB1nU@cQY+eBJ#|nNgQLa~<)A$%G;;qWPsiTATu$gk4^a zBb;~{oUu74AFk#2yMV6)D3=o6 zaF>RaK(WsB61|E8J~qse37oq)nW`R1Sg^k+nr2~pFOjl48gb>rt#lx0fzYq++^rMyu>SAKkia=b^*YGK~h012q@1xO&5FD+&z9$)xOha zlr-Q_)pT7gMgWYxnKr6xF6GJ<-{}#ih`Mmvw)-PqJoO>s<`t>Y2&I?4T5p4S=Zo*= zi$VUqm$yr_+PeA*?pap-ox7gG!_^;?e#`h~ zzQ?*&`xw{<@E2BZH+9_-Qc#Yp?I#^+o~_DnMsm2NhCer+Q!?G*UbwWn=N!&hL85xQo3+o>UfcC2^Vis#HT#_s<)m4cC4laT^fyi^+VnuQVyff~;H z_yd(A3ut(1*2{!dZK(g!ziiY0<*@Xl#Rf*P7?w><%RW~u@9Vi zi4<@~Y7evbpwpg&3S^99C=TxEe1+F$-sze#ZX2Z5-UXDrmt;C}(UQDUz17TV%N*k^ zg*9yU5meNpiS+65KjYD7%D7!O5QY03DMEkeN(8DW_D$=|r^k)Xla_6oQ5>w{qB_n3 z$*z^Dkwn7`o))VHo;KoL<>_iTeIKat)d{Sh1CQdmSv{6qq^jZGNTbQIa`G#sGwRb#b~l5 z&M3_#rF_jw6Q#2fCRW?DoY3n*J|V%5>iEbwc~__mOOz`iTH;XZV#57~P4I>c0_rq< z#V&3-`mWq1=TC!MO2(ShUNEs##R~TYvF2b0zj{J;I>UujLVmD~MMBh*2x=pXMTrVk zJ#nLinPR#gQ`N?!)Z^;c!@YS9VJ zz+AQbiN@NsX9Enqw#3!Wtwhx+Q@(`<-}UTghq#S5l5W@vEovn&@g+YHd2n^HP3>k6 znk}Kj>>H@1K0ltUDFcVVsx~ZZJRhH3c|8JkW?oyjwaqxc4qFL4v6cFU zRdOJ2kpb%(d#_mJeRmTiUl0>9+n{`QC8^AJ%&UGz_r1V*3eW#7zQ80~2xFL-Jk{Id zB%&QN)~AUMlHX??QT3dz8dl=d4^_+I!-MNyfl(!wq*qaW$kb`I3u949U%JT$720o4 zzR*wQl9i)@-w+# z8+l8`wRKB-N?pX&5^g3lrG-P!Z6mK~npglbFDzn0 z#L2#;JPtQwi7q=XZAfUyRn_>NyGW3-%E zO12@Afg%w(G>lzs&|S5jzg7COpjATY65wA6GAu{y{rE)cu`%EM4}dg4m4CGHZXTxK z*!lQ%*fU+Bl0~GErKpgGI%I5DyqDYSc%oFvSW>gi!muY|WPHvc5!+&yjc3g;x0a&H zi%zuFP(}n)nJ7k0QDLih!X-0PuvQ}eY{vb7Dy1L#d?9*G-yj#Ac!&=6b@_3HQ2agj zRAoFN(+u5}v7h>Dv~i6ErraAK)F{vP^tWStUY`pCdz)D77{F>ArPRK>s*HhaIWvCv zrAJI}Z*#s;pZxux!}k}kSKV#8KG51EwFo|S(?D5{BpdJ3W0=>hQ~WKCLsN2v*<@mT zZEp8?lIG+1#b2hlr!5d?_fM=eA`-%1(c+ML`g`qfZd)uQo&0GDE%flhs=_PLxc7rH zby@F9S;=$t2{5Z#yhz7OY`qd?+W^tPvy1^LWQD)QmMhWHNUXCHLt~Yv32Xe68)k%($3ML8uyW-Z$ps3uV?rvZQ0^)`J8yXiekBr$!c$3r3oj#DT@Ouu&s-M2$<~lAYy!RK~TwiXZ z>n*57LI-pOPe$V6^6A}bxUdunS5&;}SsMG}Fi)0h;~aZz96g>!Dbaf#3~($w`v>Sz z73^tja4uHk5B#8qMsMAV9q65HjCd%UEa-R%s`M3ghG{x^5HT9M9s9q+_5 zBJNOsQkJPyMPM!}AjztPDUKly?0Zehi_I6$Bg!7w&BS@L%)+!iEoQN``v(>4kH_;5 z&{A7h3x4kx@^>tl#}W77wxC{{9*3Kfy%p7Rjo{WT5N`66pRjl<_d@$%@bn~<11yun z^gSp=7s@ch;Muua2Y4L3xw$DnydU|{Yvm(;h|8%`(0y!)#^0a5@8bDlcj-zKZeA|1 zv4K87dSTWd)*uphT_yCLoP{ywMv{1ql2aM(rkO47uRm(`a&7BI+x};g{0GoheeBE} zj^WBK=a41FPYnFgnyWPP9v__iQ@j#;h!N*dl*vAT+a(j(W zrc#o={CT&wYCQR@u*@K@gKS!4ZZ5L^+Gs_L90TF%cFrv^AS9`T4BiNJT&Hkw&lN=# z42a{b1m9g9lBeQ7?@HJajm97pvXu4HEWU$CY9*;I+{GO3z>9?76?QA?br;C_kUhwY ztH(FYai&8&x&HwAf@3H#wY~)+gYsK~PQy8MQ5L3QFsWEVXU0LiLT!@9=ToSQcjCCw zz1g*;^FIJ4AMgKF-5?p(d&&ITsE=_3JE{{U z&Q$h)s|ueaKNY^#P<5BALsh2+qYexLsMl7sTgl(?M= zpS1XcxB>*enS$oXgd{syuAp`~?fnMzQbo#1QjJsVH1O~Fg8Rf( zd=wM|{Y3l_I^9lrNEI@}ciAWdZ)F%~m854$9dO4|y6A|@a10l zG<`%d2&_YZ@H%|`^l!1n&FOc+*hSr@|DD6c>fNWt=q*t^ay`qTo1q#Bi zi+VDwMs2Ci(+l$h>kV&?Un!;aTtJfpnSQSxFSz5N>a@QEr5yTU^{ZopI+ToC1A|pj zuD{gTQ^s}bJFjg&s@vu3FeK_lz;o<9QyZyupre$6ihK{6b^*oznoX?Y-J2bHJ~l6~ zckj?7tW~5tu#qy2;`N{=F0F^N36DRX$o56%@(Mp4Xx4S%we&&KzPL9tF1&?KLow~6 zbN41?tViblwi%1s=s&Kj7b&4Kh?LK0rxxrZek3toP*$)0gzSvN%)IyKChSEV($y49 zQ;s0vTXkhj>h^BVrLt`0Tf}s98lcZ9zD)O4VwcdqjwR78N@Om=r!RU$ov67K6nC+ozu9Ew^=$S-H zIdKo;>mhHUQ|+Etzn`^vBoWDI8o&0Y?Q<9)n?Wbd{rRzL%f^fCi<(q?tkC1+J zrNXDc;Jfv)#%Iso2c7y2)x_SL8KrJ)bUEKQJ>vODPKEIE4U^W^fthLELd_nNlYw=o z-Kc*_^FH`7qpj8DxnI#ywj}J$6N>6w2wK0J;Js4s*A$QH&9dCI^;T>v{5-y@!62P@ z+Q&1tX_e5REFhmdD!Ikq-3MFV+6Le|tjkc%kzDW>^vDs)ywG_BJ*C91?1KjnESf2{ zXG+|5xh*E$KFyF98ZM%3s!bbvtKg%iBI%pRNT_*Bn0(tVkFe?N-%lVVT3#Lfk940P z1>OQv(VQuY+qhv5c(E!lc-)i&O!fC%Voo1z-uLiAN27HWGfr|BL4RFWA`{<+k^Jqg zI+nKA0>uLqg>S}rkbRrV70S9({G1Y!e0}thdRDC#fTP#ypOO=h*jJUWw${?b=R?Tu z|9btIwz;<=2MVi^$@~KZpsWm?j;rrz_*B5Tv!VD!xmd;g-HzE5+@pbf)BJt$m+B;? z2hRp5wa?wIgs$%9`5heG9GjP;%JJtspJSvlGHJmDdtf$TL|iaMGdG9$ej5v+eTmy})856uXES2drR zfb)FV;$=Q%@Fl&JaUwg=tsZ|J6Mmwqh)6J z`=gxB9DHjFZa3ztBB(`Aa6lklYGgf(W#FY7W=mUHys1iUIOiy1d+tjdJ;WAdNt6qC z@;X_^_p+Jpw4l@lOEH8B0nYMaO&UJHr+W7WKcoHYiSBO|JS$jXdyoC9xj+5U(s?0= z2H7tWG*7RS?z-pX8rmb}6n5fLmb#SR>D(}`wUs9Qn1$7dgB9xSy~G985V%MW&E~1p zP1&*g*s|FrgAG>cxT~)7t{bOIe(m0~S7o0yj0ckp>x^aO+@<@4$E6b={v4wBWSk?T zOrtc@@XAKX7hR1Q&;ME_l4jC%{Rrvw$o9vT@uw}=tD3PRe>UeWWmrw~aeEsg$8`6F zH)gT&^FsoErQ$Ct-9v+enx3ahg=HpK9EvwTcsR5&Y)u6{46X)z3pEeCd8RM<4gJvY z)qeN7M$GA`xo#5cmPZ)Q&L^*p6vi{t=HkMchihVv_?=OwWFFuT7c;AV>G6GoO=I0U z?p`A|lrbH~QDYK7hjiv>8$4qakoN#Ui5Exx_4^F74>yW>DD%f|>f?Vg(){u|UTSlC zry5jC6ye8sq4=QcTk|q=%6Z=;Au5Q{F`J>$xVYkJ)OMx(2Kd(EAg|;}ch-I#hogMe z=+2%Cd;9m(v7}nC(Qa96fxM!)+5rXbLcC>p+c;Zeed>WG4YybgT{Kmy(M3I#GL*1^-rRjP+DvkS3dop(9R6qOY7Bt*Y2%@Z^!zD39*^o*5adN6HBmGDI zv8usMiS^7zbLroIfH1~0cqm^2Ua>zYU^&ynO>pENAS&lhU)hy4;Q2OTcd=aBTe*A1 zd2uzi<7Uvndj%|0SvO%Nmvhm;Oba@Lg-KlrGjw4wa~;G7>y@S<#tNO7M;-h;)QI(o zX|*r@zVTB^E6~FzAIw@(@SD4ymbgeJ4(x$S#Not{wGv|7?RsEecn3FhUQL-*yn-?z z8X6dW4gM%5NEzDygi3EXNKk*SSD?x~frJm}r;%l}C1SGWf5$EjqBzreVrbVu-8WXe zDtk~sa#YmyPHw%{A+O!e9+BTQQMkl2V@HzaEWm4@m;P=V1)ul)wDeGz)%&N3b}WAa zGCYdcTpn+4b@YdWn2_4V_IeDC#Up`(3>|u0VrUl7gEXp&ON&Ip1)aDJzxfehom&-n z$Fq$6W0Ib0OYDTcEj965ev$-9@`wnX?X_Yg1MI_($VF;rU|$T>Id_zm(PD6`y=zi} z+P>N_&t&v29C(F`Hc7CWT2HTwYW_$7b79Au}cc*G;8s;k(PsPx0ur=9rm_f;95 zS5&WGfM21AiBTecesEpWl6q60H+RtF8ckwI#;{h1kA#tg%_`iv@dxXLoHMJ zrUEc(0p^@QQFGGz3KrI7(kd_&ILGN>-PX6Q)PYq5phWr@ zeKi6dcoLj06sx{C@TWiVfzRTvHqgp@x3Wrl=UcHk#Tk< z&hRA~rUD0#|B)58;T)$O^$QL=;;f@(So@q}`n1K(R4b`4b9aZfzgCe>$91oObU*A0 z#;T8Zzkc}8P)+{6lhAM(JGvEIzJRi*BU`(vh`wD7#`bWKsf&cgzrp`fLhH72M;O-L z``G-Tmd$iVmbNiUrPDOS&#A;}rM-d4xj0sziG{gV&$ zXu2tr$!YZ^9gwRWTYeI&qm4k5T%@ZJq-*ZRlr>Ye(jnt(TAms{w`FC_Zw{~94`CiF z*;g0vW9hSlV6+GS$u?z%x(tC13lid1_o|iuSKfEFHPt;|2NjVfg7g*z1Q8Sgk)EhX z7qHMxe2nKs-kc=o+WVZ@ zGkdR@S?fW)Ika7;MqqC?@vtdOMP7C1)0de(2iKPuN(jfPP;{{=i9)P{M!}d4Z*!c> z%jLXtu=eR6$jA$PGx%d7q|fDV;n2}ou3*t_X$`s%AC@r_3?IM>>bev-CGH7+TM9pwq(lzI$yM4uU2Ky70H5S59 zu+he7PZsm5ZR%oIVcJ+h?#+py9deUwmz=J_<{;aQ)$IeWk=_e$7Xp05`WQZ#4fw;s zt8%|da0BXWT@|+W+-R9#mx5AuGAYGTd z1#$ZvQ6;|No=Kg~;jQfsbTbd96wogv+A4f>b;nbLDe+qADI>6K`UA{M%9-fIRIPS^@qfx z#H>P?eq5$ny$5%%PYJjK%vn^dGlje9#J6%QKMmffin(z%DePkWao~&HdrHS__8-B- zVxZb8D=#ZhPzO`Sv1*J}eUDNlO?4|$gVT($s09h%ZMB9Fh1Ev{dg`6Ife(V8GkYL- zw-}AX*q?_`adiLAr2m#J<%f!Q{?9S4gsEd`{OqYlEkE`iaj)ooRLFX7#u+zq$z=(Q z{C+1EqUbxaZo!>j6EJVJOnb7I{g>rj!dtfA85~Z*JmU(Vzh!jEgS$+!NG>h@9fhTR zg?Uqg<(3q3z_r!=c39c?^~w|1tr5w$U(Nv&HjgEJ$T`~z%}7j$`}KL2q=~DOidfKy zq^+;BHeV;G-A7E&g#+~K2zE+FOTJwScv)R65iN?rM>2&*`x{N^dAPYH@fgthpYry1 z4L?4ZyX0JqD9mkdnYo$lxj!U$SWx7w>#!K$bmLp>)*cgO=%Hm0vtMFf;r-7Dc9ImE zpvR0$S?zZL4d26?-*mA8SyLp%u2WCi8>O=`t6aOBOMg*3@Y>kKD6^3)-@(Gx&1guL z)veoV#*Ey`p&o`R2EoA78&3i|Ex5mI# z74b;{;tgFld@a50Zy2n>3K6AMo2MT)dkJRS4o-PaQZ(-r#kih-fF&kJHY^3pou;4B zA-d6|7tz5-$NxY&%f*?8W#Q_%gPA{nME+T2XxmK|6s$eX2Rf;ML{fPqbtW@iSEG%M zMmVc$?EyGp4ugpi-Zg1USH_Je3%Tf>JHILfPIOBnH=ic*X_j3u>3=r)=?Blc%OQ|l zJi1Df{sptNwj$XsEUXZEdnLbDO~7rnMX37)BB+i+%qBfiy^f^sPUfBY2iom1zO%X{ z6)PVjtL+*7QiOrx4=!bCCVByJ?CTs!4qzo%td!rRC8{|sKr3hjl{9tYT zqQ<_xjl>l4M{K`Nw0^8?)|^N zZ{D%ndoKOKUDQ9dsT;#nzvOgmNCEiC;N3q>TU_w0<;-=A<#5PvB4k*o9PWuzi*zo|$+@6N8B`Gd*d&*fffN_0UP#b6n z>$J8ENy8{fE$QX2nPp_tjs&fSc6HEzR3y=;^bPJ={>>Upar`Ju7D-7x;I7eYG&+F<_z0el60~QYvRH1b76q4EL*p98)6oJK^ z;thnMGU?WSije%}k7Rb`j@|x+t*fo~<5vVk@mt9{EaV2gA+QH8nsVeqpgejZnco<^ zL>fF2Bq{Hn2V}%+(Y~)1&R$>>`ZK(K&4{iv^V7zH?t+@R7ixiGwF^@e)VC$loj?Hd zc?GPAnDNhM+!(K2{~k%2@579fO%7M7^qoX{C0`kLGQTxqcQO{yq7-}%d6Mu7Ad6`S zP+x&O2~^bgEkbEIJ(s*}`X|*vl24(z>ig2Nm>Zii2A(cQ`UsNfaWiA;&+QvT%NnPznf*=304$TKpRoMLYG#sT!{aWDE!(WS-EK* zN}(S`%+CUlRm?ah4EhooYE8RqoVcLM)jBe{erg5q!Rk-uj)f?4WlfG;@jnn|r|m;U z;vYhU*5j^5e*%EW;H0wlUY^_LYH_^r+S_z;J9VqAgUqBT!{ld8Wlkl_Q*{qjqS8Qg zpv6oMKJpDBu6;ROHF6$FA|(L8`3K{`q6s|_B;$}9Q!G7;iS1mv_jm%qpwU0PsTIXE znQ6Mo^I$%h3SdYTM!6)P%*=)UkCbY}Zgyhg7VFCR@r5h0Lxvqs?O&#S6xbNXH~R}6 zRJxx5zG6`ya&h=`ch&2IK_Jj9>c)Mn)J%88T%6pBJrIkWPQls4B>tBAaA5ytVJt#` z<-gw;LkZlYAIYWAW1z`7#`toM0VKU5!{bTPtVEO-)8BI3txa#?Ymo<>#F(T`(dkuc zojhp-MehU$|6N6%I?gR>3WKXOn-RPX!cf2tJ{5Yiw#WQPjkl?Jj*H&y(4wfD4f&|2 zJat#4yKscAYH%ldwIW!(r*xSSPvonQ%Kb{WGPEZ6CK5li4C*I_I-SV|s+57$e)ME| z_aCgDH2VJDI~j0$>fAX>ko{%&_otEmMpaYaNwy&#+nHO9i|BGsCdEK0uykehaM$9n zu(G#L2WC1g7a_Ii{AEgp3O%I%ROL%WBA|?siige?ip`sZJ`prHvd@4W2mhA(2jZ|a zxK%Rs4u(7tKuy(Hm}$U(mIK*E#1(VpmUjhjL?8PuhB?72tjq~)jxHuT zg!y5g*IL)uvb%Lb1Fr2|b~$vwo+sVTHl+5v2@Phq(nY3$I(K}U&#M+DHBw@*?9SIH z**H(#^hO`Xn6@}_@Je-zg)zMd{%}w67X02VZ4B2k<^+{0z0QVkTT_yJo>e*gDx?c{ z_pI$!4-67BKt4VRFd3rWskCSc83uCUuOIiVgDPen;fHyapYrUBHZR8dqyV`CsZ>SmLUL? z_=dfovCiq1YwPMvuZ_DJ+WFMtWT8ndhmryuJsdn7CncNUH8vyHuxa)om#7dWhT=SG z4~qHT2T=8p{X>=+W`wd=+S2mLN=0s*ErDLWM?Sb|$y*oFTB|;3?vF?TqCjJ5;A4F8 zI|=itI=A!aNsekx?!UnrbYpfS#iUOC+KSzzLcz9AmeZQv@ib|;m5T~sTsVAnY6QDk zPDzCDtnJVAyAzHhbsJJXHKJBUu4tc}5|DDvXGe~tpaNYcjMBaGUZzLvacKB7yEhdQ zTs2IIiZqz{`WA2x!Wn+Eg0A&Y9CW!zD1pa|; zWy?*!d)F)SN(*=GjmSDXvUZJhhMzh{Rj}adHxyh&hhN<%*7`15oQz5EFGWLZ$!jJ@ zFG-%M4~BARH0VxWlUdHT%kyIw#Cub;ffEc+k5}!eZLUoPue`}nCN@%QiOGcYh*Za8 zw&F@ZqqCnX;p;P?fFTF0w{D)tvebQdU4gf!3hp|59uwG z6_U80*0cS}2AU%>==}L`)y(6<|3E<)5`J7i@l|}3G30H!xj05-+oLXb@}4g5uU|CH z)^{a7{T5{{!!hB@wF$RnV2$U&XTV}NgahtqI$_1E0!~d;pjNFI_HK;5tD|ByD?auS z4~&WcZs2_tg>}>#1MOR?KyAEfX&S>OT`Pj=vpnSk27zxwk&Rp?d^L4O$0Rx1LH|H` z(TJ3v`AOqZ^)9C;e8&Byhu0n3fth<^61v^Fdm@Ajs8ykUMM@I(tbgpP{KM*KqZe7| zg(>?~IXyB*cK30yHt@Ki!T$I2;@gS?T(9w;Nk}2!^npXYM z_#a3bN0$)*d7A@TMR?-^Ida6gtAxP^!%ZFK)WPBz1WdT_>;;R9XA_P*z|!Y8^rhka zfD-RM>{H!~*(<^i(5S}9Q@KE?ydSaEODxAzWalq)xEY3Hh))U-_eM>?<6rkC%gyB| zfgd&Hv-C|o-clO|6PgHY)s0oGmM@o#XSokA))(LMt)xi1UMHlz{Iq4={}06Qt~Kiz z0f!(qRt%`O@!G;SHJg0;n8W?f zHZbFq_Ak{bS9rIgaQ+Z}4g+OuQ1lV(mNZ3Yrg!ei4X%SLlHdD0q2z1CKLG~0gga4n z;jgX>KzEX(bJGYp#qeXPeW?85RdzG()>VF=67wT7tEpu%#d(vpuc&hQ)(L$JT)Fgd z6R_MD*6&kdAskTHW#FNII0logygSbu`Dlt%=&)pyp?&0^*b%WbE_K=pShE>jw0X+I&^0 zTWD*-b>RD4AVo2m=!F}LuNr3Gt+d&J1Gdm_JQA;U>ak&F9ut$L@ghGrxPax)DB-3h z3v(~>>=IBFwA&K{`-36y&mnL!asNOs{~MBJFRe+P5~A|wTg1nc3|3&9vyI^dn9qX6 z-qXoHL#zS3+V2=rx|%nvqlg>x$WSc%ntw?;A^mpcnVueQMguR?+Yml^+3GXDzi~4u zATt_Smf=qYC{#Kco$tO0iBjQL*ZTcyRUlJpy3s)>tgKshEz8axkn*2XgWYPk4>o+&;41pRKTTwoI5U&fr&`T78zR-9~7 zXf!r@dIEl^c{f`pJ}-fag}1>jLhVzbZ0aI!W*G~zY8>-YX@#EC^;h~_g9~^XH;D!mUV%EE3Y9`uEP}q}8KIPE3qL;wWp`g#yrf zzo&kgfzY8&a-BSdg4ji)3X;cs9B#_N3l7FAlytt@-P=xVD%QW+Vhxx=Sj6)79Z$)u z*Q~Q@c=u62xtfiXRhgtGs}nlVIC*glEUAV8^fT)CnD0;NmFwy{l7F&aVZSLyqK2%Qr%Ac z?~>Sb*{&E%``kh=@m;Jl54vn5LKVizvG6$u%Z%A$hR3zfr>QQ+Sgie(s3F2}()o!s z4HsP^PCf^_j8?jX{zAYHl6d_e&}Bv3IDL$&APL!lswG8m6yDH4MZzAHe+C1 zK2*$Ww)6}coL8qU`6G@Y_5mbX-Rray_l42Q&|=EZ!Ds+f8>jjAw{@7655yIKS8X@i zO!g*C>n}Zv{AsJW@?SkUS-?mGdH!^ zN&pjfuTZO@rnp+_Y>O(#-`FqkIPphdD*8{qi>tf4b56%d@L|_xwgUJ?G@f~Z56$7i z_4#7DE99@K2E(d|kKGAs1Um_6Sve4J>EpCmFHv5&N=D=Q@22;a5|36SI3CT1sNMJ5 znElle*f}`I5-3$-N*Zj@4HBnuv(He=FyrJrPn7I|GMwxmMc3{HE0Q{7H02`!|A7}l z4=Eea{2ljif2v=V-cTYwc#ChSDthR@fDtNTUXKz3c7ve*KwK|2Cv<*jcJtn8us0A|e%th*Pr-RAaV*f^h{3b6>jqJ$zA6V zabCp-ce@iR4-^Ss&sZrgtv<{$FhDv<>2?`-V!I>YVuA=a_g<6XGJ^IHJ(7Ze8_?(p zb`CGyx+F}Ic{!TDYy7I}>?T=um+5UcB2!y_BCY!><5{?ah|L~YK^RkdP~=QV*ZQ-L zTlmdmwHZk7TJ%sP!1UaoRWY8QCFJ^gvvY(GmRBTp)XoF~#T5X7Q-3$;`V9d8=oDW( zdO$M0@{>rO2kYqohr}2Yt}*9#z@Fg%aPdb7d>^@TSFfhr4)rzRJ+tSo)8MZ`UU6GS zPffW~oZlG>S)j>vl=RAvrQr9SCepID-5Fb;;HafsQ}~jG0R32r!G8Sr7DKCN2C~@` z0QsZr{vs}zfm4aUs5|~eCQk{AAt@03W?zAxkL@9URd5;01cJ~rC0F;?v*^j)2Ut`- zJ_xRRb}jJMciPVl_o?R5AgS$(bn^$)+!uAUDI*s7Kp5-hLo>9Qf>ItS9k*+9MJ!a) zeiIjrXfm;9FU30SKg&hA#`0CplvotCg_1+{qRxfi(nJY8M@eW*cZsTibwT zDM2?)h@p?hXb(~0>26;+%)n1;JyX_Ayg$-Sds%cI*^<0rh$H^g_mh_zQ6IMU@#-on z*@X%ci+0aETg<>2lWj?p_MX}Scb#BK=TBH(T8b7f>{KeNzpl5V1N}sg0CF5aOorqw zmjo)SgaKjlb9&c*v78-RX3)xrs3m-+qqMmpNXxI+y3?GCSWjZFXDs<8c&pMHVpD9M zT&5dudbUJ~4rc4RJIk94K4Pr}4!DULus?S5V_V6@hRvWuT{KnEV4^(e7kpVT>y6CY zc$dQ$NA#|9futxzqK51G@YbSG#viF4Z(@rHv)VjR4YA1)rX&vxELW{m}fI_&*{X@=*W) literal 0 HcmV?d00001 diff --git a/test_imgs/test2.jpeg b/test_imgs/test2.jpeg new file mode 100644 index 0000000000000000000000000000000000000000..cf0e36746364c95183663f46d50ed0b1fc7cd889 GIT binary patch literal 3895 zcmZuz2T&7Ow+x5bQG`&1 z0Fk~ZMF>Sm5FsFjUIU?b9=r2q=YQ)vcjnId?z#7zZ@zo(%su*g^c`>(VQ69q;NSoN zIF1M4hyi#C;Nv+dEFugP5f%Z80zp8Kn26Z%3<3egfMODVVUU>gr3(@g3X&k;Mb(Q6 zN)Q+f29iMH5t(>_chYmUi{K@4pjwr8jvx5ECdGX`KT>mFI zfP<5p>%?&gEOfknoSf&l`u~>Z;1uE#zIZ}bRqaNgg@|*?3R~`I7;wz@m@bzPKp()m z@DIsjC*hkw)3fIOkU*fESc!-a)_liR+HFrRaapFi-oS9;@!Nv-)ERHo7L#&13ij#i zqHc5jw!Kt%5#3@o-FMSINlg4}&8qZs7eL?pGrJ zY#yH^vu}kV-}i6Mo!)*&Uh+0zd}*)PoZ>h9>XCbBok?DyzWQicw+q~6&^EYcm9v&U zawzPFTfJTOY10ezDK%U8JW7d;3YE0hXd?`fa)uGjyO6iI4E_XzE6Zf{a;`-wb-Jr%sH(SEhxZ%CK)rzl4j(G@N zm`}2qz2=vWDIl)HF69aQ{?ue`m?s`@drqNyp>q=Ys=G;0@DoLL*ZSZfCQcPQizo_A zdJ*M7#e2`~p6gVO$uJhQ1XyT1!_mS#6Pd^_G5!c0>tmL?eKoaVknoWqq9sA5_LTVIyksO0z z7Df^@(b;L+GUKRU5}M!x`tqgGe1?Uomgz}~^=pb&z=wQ4NFyl8WwKdAnTl(+Jwq!| z2@|bCba$8Lp28gTX6Be4pvH#3t(c1>r^4u$@_E4>^^;4)so5lPBfU=Felu#QduMQV zWjvT18dsmWa0J*5>P>f958RH#BMw=iH81Q0?&9Q$44oX% zNBL!{_3Z9;T6>lsVcRdgOoIEXv&_v{esUh9@uaUE#mr_?VI@mq0Y0%#q0+1EYwySi z_!!^g)19PRy%V;knv?pS-z^d6c0yFkv!vyhdyW9I_?$>)h}68Q*Kr$PHTB@ILkaOI z_`I&xUYhQGk!PU&zAitLjMAgo4^(>X`VX0{*8A}YXEh+qM=hi6(M&vRoVIb@+24ul zUF;4+}s5jl855diJpwwft=ThIU4ED$xv=h z7??Yz8iuZkz9{NU|MNx(zvZUAoTS}MF6lz2yRaejU3|20!|R8>ZmhCbs%R)V(vc~u zu^-bDrHQmGtvnzb4~IL7s~1l|F_E#n*>0iZJ)LW7fmDeTgI~WLV0{I{DxD=Y+r^Dw z4olq<@NnCOS4uT-OVw2QQCyMK@`o=GV<}79?t_CDR&~y2{GiK4N;_}i_l4#;*5uf( zHL!lkU(JnJe2z%7M%knowTs+MtL$CZ^lg8eoyX8eLt;avR^AV%P8Mfp|FPSKTB)!b z+Uv=GYOb$YwYYM)IRzx786peezU9wL(0*x>Zz@vLDFb<*TkI&Y&zRYw3 z1-EZ>>y^Blj;<|5N^Y6*K9u@NY!0KdG)(p^MWhps*HUeIY_&I(n%75b~@oC zGPNBMa&7E%)-@;N#a(-iSLeZyn~?Yg2sDf3c3wWhq3horsgzaWUw)fwrhDci5+sr4 z)|4QQFgXIKnVWX$dj>Q$WUL>cXwuIti^eY!6Q}(8@U<7V%o42|Q)5pTQlCNGnbTc| zMKpKcAZMNF@FPH^I>urPbEgBtT4#Hd#Sg#7W;;&zReN`XwaZpXQL2mnVps&CThX=n zbO33KctF@E=R+i;Y`V4so07*qDi~Wv^9Npz?;aDQ z5GG%S-mLISZe6mWWny0|8IB!4HJ<|&i;}c=du7Zm*%^xng8rC4u}9|~_E)-@y;>d` zk~)G;Sm`+|$hinX%Fd@I2${{z=Op$3D)9po4}`V}Q0fNe-iH?9863#_XQ?Jm-=4sr zC?c_BYePq$Y%BgH*URvbZ)|QJ6O0R_IN0=uY4Vbo&S}|M_~kISBfu~*gt?qc>mCo9 zV-C(7m;nTRjo6vixj>SVEen)6& z@tQit?^%5-I-w7laF7f7oan*I-cg%Nua?fOQA=>#EVkD!XnniqP@mL!)iZfo+*7Re+8oht+ky@Z&YYKhwUnka33Vg z+{5CzcGe3O%_vCzLjfM+|A#67z?I|Qdq6vUet-%Jvnf-HjlzHva>y0fHKdxTF?F&r za&w58yOxVkqN_1AjCu$j_u_BGk4C1&=iU8aWktS_S5;EzPVf~+-m=S+DIm1Eq(2Qo z^w^5JU`f#V36x-S>sDkcYx@XxJiVUMy4nfr8fPI%=rN@Jge%)#OX0 zzNhoa6z`(qK{*;K@dv7QWwuw$(4ofsakW(wQd9Ev4oQ(-OG8!rx;OPE2c|Zi)IcCj z`O>wB>gDNAUvt`*L&T7ev)$3wQ(mnhVGni{Zw)XuFjPmNRAxe`f6mTo`H49dEJoYG zz&)#XJVIOx?u|5^0v`bs4NMJmlKs$8Gy18SyC7H7w;J!=wVI}V!|wQ*><_PcSh~2+ zuu5J+bmSz06TLs1rzp9MkchGaAn1vE$()yd`+i1Y%Zes&d)6UI_6Ptd=SzSo%76Eu z8xU?iu9l{LdxolqN50Q%HH_M}>rpAmy`Ch=k^%A+eLy%0uGuH+#yw+yU#|qO1tOl~R;0w}KTBw64@-BIu^NviltJELwa~+Ya8?LHok|#KfmV%&e(aE-V zX%zayfI1{>CuUW7oXDtHTQLYXxysro4@&i8ME|F)$RGgzn!P86dxG{a+$qj!0Fl5S zvtpd&PSukOY9R25jFCsrp1%NQ4#b>K!c1&9k*4&==AEkWs_b%RWx6f6Z*)y>WW;XG zsO;lf@D65~&y;Az6F$X;cgP>u?VUHoj-;3ibUl-Lan3~4RirI3HNgtd9&jo3bOCW7 zgt#D|`-E;%m#idvL^4;>G+0`bo`@$U(clRvn+cR#eVPUN7ciEva8qr{))#Q4gC)%j4%xV literal 0 HcmV?d00001 diff --git a/test_imgs/test3.jpg b/test_imgs/test3.jpg new file mode 100644 index 0000000000000000000000000000000000000000..ba579bb09e44cd29dac7dc0f5710606c63962b21 GIT binary patch literal 29904 zcmbTcWmFtZ)CM>(I0OqM$lyb8g8N_z8r&Tc++}c=pn<^x!AXL}g9Sau+4;L5b)hj%LH?Q&Vi3wi4dQJA4 z_$>)3DJdQyIR!Zh#Tyb*lK(nEdU+KM6%88=4Vwi26+X%T=k%`=K!AZ%fW!qvq6Hum zAOQ)G{`CN;UgSr8k@i1<|IdVk415t19Rm{!`=vo0J^&f%f22o6{cm89{9c{|PzX>7 zX*ea&UaNjar*$Uc3X1=QK_^+&MXWY)3g-Ue5{!xU<^=^A{W}ImCT1R9K7Ii~p${LW zq-A8~fdnY1G@NLJ5~}E*onO;(1z`|L#{a77 z!ldI?J0-vR&!i1hLcfdnrz z?7=%O9`?O9yqtyb>+dKg4lKssaj2xg3{{C;Mx@%9ndJEPD*!!@8_~&WE`=0;E4~>^ zj~rx?ij(znz1^1Bgr{8KG5kOVyC4Z7r1QZL7u+e5YAAC|kj$-_Y9CtM$;I^me z*d~rCMWkjzq$)*?g#mV!0v){zB$r+F{+}PiU@F&7N^}Tv6-n!!5s{z>A@@EYQCLY}P=W^4{ebV^#B1pSk1$T-{ zcRK9aE#Cq zVvY%bu->?%n{)zU-=S|0Uo~F6j=o$7_!c!?JB_A62t6_=mVXFh^{@;&Qis#PRPvB0 zMmZA?6lF(U33lD}2Kr-`_;Y~w__qFV&Bm$#(ZTg~^oIh*Rn>*odhA+ivvs+BA+5UP z3TFV;=njb3d{pM@{%@cA^u_+VW7UzjEeEs2^ISqUYeM(^D}Wl2JC7w^Gb$AYsq+>NTq4aS5*Vph#V#MCknv$`z7bp5shPs zp59MR;jB`8a)r;nGh7zgDB8QB>C@w01FBsDfx2;H=J`j}k zr|HPUzzS+^($hjwt&n|>_3&_A^!>Z$++_P7+lBpwp6i)J-+usiIT>(3b^F!!eO7su zS0uIz7sbFs!9&REOltW7W6Lj@KD6cT3~$8j!GS?u&m`xCnObq<`Nk-Ru)kZkR!JfR zBuZXFzG>mIxZyR8FE1B({?O<1a~x=hZOTS;?Y&QV7n*@``Of{BfdGUwmz-! z6BCD6mMNu03|Lr5w0S!b{#v1sV?Fi>rSfR-wyl(%Mn)1b!O1Qv{Bzvt$hqEy{&TF% zYceDjXNCQb|=Xv7{!ePG0$JDSTadCzGd?45#z#zZMj@EOZh2 z5~T_Ud)mhrUuxMs_C?ZqQOL$PXJL$0$j|Y0Gz+kP@V?G}O1HuHAO?~Um1~8)AK51U zqC)vK8nKWsiFh)xyIjiTV(wn3GO&bw)o^qu+^lYjX@o;h6lEh>U>5*t8oR6Wc^{24 zrNQE=m_dINJb_}J&zXno9_C!!w;F|;eWfY5LIBavw^~IRQ$cn1-uU%1a0QS4e*m(j zn!ni?BTP<>-Ino}kb@+n;17*>8^B<^#uE1%eRhfcW%64WVa=SVJf1Pd$-0I@Fo{(v8Dpg}K{W1FLE!}8{pMw2-TS>#Xo3m(7 z%-~R$VF60z<)!0}AyM&pmNXrnz3M^tiEA%$(r;TjwLmEWsNWX2FH27*IpJT4lE2o5EgGqH5 z-;|B`e=}5g;?Xn>U9YUrNG5;p#1-LeM1c8l=#2#!I(ySVnTc5q6K}u`-SkBaD61d) zXs6oTpClIC#c#?v<$fS{(h@tNsyNR-NNa5WYsRl+G|IvQ(J4pVab{{uCa<&n z07ZS-UoS`!oMTOIXU?rF7Z*+v_~~7g5W$fB$-O?QWik`fU{A^=_vhNuem6qFx(3#K z4!SRR3jY8!AM59Z{S9!7yT$U{2=BCFcR$x&XT$#iDl`WN zuKTyZQ~k!Aa>5<00>w284q6!dORid-ymOzv)SuP#f5pYv*$u#LvnlKQK^i3AGZdX! z(of81E?qYI&XzyAm_q>M6F*g^LESgh$O#{G@z%C{m(k-0D%w{@@gW<|Ryv<1R=)O$ z_Si0x?_K7`8)nJCFBcec746ZeQb_ozjYN{g4~l*uOYnJvLQ7ErS8t)*D3YBNmlpsx z2zTzC=>5^=D3XJyR=nDr2^X}(6}&7Xx0f)@9tnDELK8p__7iOnYxD>|AfNdZXL}X8W$4FtTgg6_l?qXY=%m7 zxk2>940dNX*Pjmq`r7Ts-5P3}IaYvRu8JQ*R0#FeC0Iw2H-9K^)8&Y)ev4O@*2mYb z7aL=YtK+kZ%=O+`q71Kwst$5q22_fV^h*}TF^wIZ)F|Q^M zW@xx@e8Wn?YC_}i&Q|k-8YtY8Imzk175&@%nXH;qd7a@DF*VC;^Lo4ajf-dBny0|7 z9}DyHJK14J=9UK3s-SF}*@h3K(a9G8a_6kKvwOM&nFK*amMG48Z+?7X>{{N_=X(>w zv>Kn#gf4*CyPfe%B)-!n&Utm-DE59_Ym*KCt4L^SHBzL|lOpsJRBK_p4Yhtvk4J-o z57E$gQ{tW+JsSOhi^za=#IBFf*OVY_<=|%X9j~m$*vNoVa27SWGds^Y;S95N0y$aG zD&!uKks|7kn`^jPWn*%99n?*uiwa_aw zOxEhB$}Jm`b6Y2b%cY?wHEMN@UL+2TG85OB$^AhOtk7bWA+8}FCe#;q`YnluL>>l! ze^`y3`PtGG!#1i;-{?G*u@iORB!gq4xC@1DXXc`}Ij`!QGl!O5d%*5Ncj z3M|{j*ymPiipvc0xA+_^u{h>pV;1V%^u2@~iP{u^n?unuODE%Z7;Rk!68Kz+JV&}2 z|KzO6&K8^E@soA6cf9D(uf*SKOA|*j6j-$b^Sq*9p*@=*4(XZSb@I+?^*+;;BbU?` zEO~IN_h284z{T8`xz$oUs@@_+wu7sl7_tpX(`v;ugn@GWwy2EdyISc}kjP3+2%8*8 z9;j56Sm%XP6t<}s|N)_ zyM8e)0MZfL^||??*a?dXFc;mo6r_lS^OgWh>ue>j$6zwcGeYlcZ2Z zNBJcHp`7nkK0Dd&cIsXPiRsPU7e#=6t6yxgxYF%PRQw*m@nB%?Ca5`KvPXZV0_ zVDy;l=ph0Z+dBUMxN^^$7yMDj=IJWSFkOylTp{0_J>w6Law+hfy)zb6%SO`-#P6$$ zOkcU0XF}|Vqd!PY^pZDwciI#IQE-2BpVTr;Z1Sc}q?UZhU2%gt$xU3Y=}#ayi*;r?A9#$L!(E~S`ElYP$_0~kM|6p!oWVg|OHNPdlU4h# zGTGBv)tI>&!Gw7==R2TaWl}1=d0pbNx0nxcK*FB)DZ;=p^gW$7Q7SmVC^TpmoeqSU zQx(0lm&K8F8@&W);W4bl`!+ba_x!|R;Q(6y15g>~v2Th4Fp$J(1Uh#ruF4c}e&=kj zUKD~IsCu}(V-3_#<3G|mVg26hZLwa23G%?r8#QJ0Vtj|VSNvY3J=seTQm{WtW5y^0$(J9tH-Kfe5%a3N^~)fF@dXI+d-X=vV;L| zNf=48RipiRzj=@g*Yo4&2F^3!_{n_nrcz^mXD_GI**-M3jmCJkN!WDPfs4rdZ1DZZ z@N!&k(x%6W{^Xw{=vJ6!ybPF67R9;O)c6B9PfvqYQv$1v3)03+T<%Wy&MM7QkN*zC zzD456mbB-O!0`vbFCC)K18~w_I|CF+>E#eWur&H);U~g;Gx{Ls3jh~1>u>2t_+o#> zP$8qVi)SxnBSBc&3@k>W1mPa*AV#f13fD4t?2T33(_zK52%p0)g&ni1%rDykTcFc`*FQE;d=lifh zXsk&nOR5B58r$HWCBA&$>$<%D39W0PAzhB5y3O`a>j%tFjq&qxR?<4r@2CC5@|?AA z$3CE4a%5_fNof)CC@x03lZyVS*%Y4wY<^{_rGSfu`~%D`RP+jofS?0vx9-PJ_3V1flFFR%`Me-_CpO@QX-%kiWZSk z^+88YCnShIFmd0uc*_17C9`u5V^;v=A=;t$M;`t&)n;YEQXI$x2WK@MUGdi0+xb>v z16F=QwaTcY8+D_?QIdCxAbr9!8E?{8nQu`VMqn@ONU4@P%`_t`4L*O;cDbNd|IX6& zBhvuIw2!$iyXxEW*?y46k)HdRtT~D_5h&2PPgymp%8|@~=hyFl01e6YN})@DCgUZ| z=whnM!CTZQ`4JlIt^^JQtN_*_KVChPtk#0hvD+iMJhvA8WK-7{?1tTK`=wM@<8_s+ zQ3k-8cA}s@73D14aGt>dLvY`3zjWgL{HN*N*Q&wiVm!+D?wyQ7(Q#e|9&qJ9$q0?8 zIpURsw|~9@NdeFccLe%E!Yhj7U*aFAer%fy%fiWj9PBByPYx5*+P6t`cI^O3kEXK( z_w*iSng+kWA2c&Opwao*<=ZF1d3O^KOZivc&}e*~dla;JgB^EH#8=qKTs%c@fC5{HNmE=)AEt(`kcF|5+@7NsU~555lsiDT+&8@!?g zydHL27?Qa=Cd-NsJ+l*j%(K4si+?BX-TT!;z{#lIT;PxBQTmY=vv zqNkncO`>g8#kb_-i0Q*>&kRY?R zxA59S3)GNDl&-(`*wwO(sGyAA4J5G;C9GDlLNtyGQKTpOUuDjN;PHIt&wB^-dD(IK zFqkk8@rc@xcoxK6ItcOk0~bETE*pOAd3YUl>iC+)z(D*if-n@l;8oy%UjzO6vEEmS zPX7g0^k>xFiFVwGRcxc*1Wbq$?PckUB{-v)<1gx8kY(^_jOpeEM8dFPZEc|{$qP*8 z@p-9V>KXuoWd!q|Ibwo8`?ewk1qFc=l|r)-o~ykh<@?#EFl+u;#{#K$ z4izX~ULaS3kXazfO({Zg+FhpTh*)?at0m7iS=;^GVDI{(EQ8dtBilxL7#9Pz30UX; zMz20N%z=$Nt_;fS1#e1qlp&gSHn=<07qGsJRO$GkWFvMQ8RemDSvSn%i`iV&>y(v$cqR z3sxD0okgllYyEvW;@P>3W`(ympP0Ivulld z%q~|HD@CN? zq@<#m+(waWV-e@J9(cIFB2JwSqcqiFADFgekA?hXc)u173e~ty&qQBGl)tb2o5WU! zxe*237C=X8JQgdHypf$1Yt{Y|Rq6p+`v=IniZ57c>y2AwZjHGyV+b==Jy<9+7@eRP zU?4>_-hkZ;J0zH`#kk!E?|wHh?-qdY;e|J%b;L*W$<8chu^WK+sf8+gH?%>N?lmWj zU7y6P+8=L+IZF3a9niRA{{aj|?OETOS{qCTA9k@|q#|6qmT-|DrW4x!Uj12KSyANv zn5ANkd(1txr&~EVDefW0+J?DzbXoeOuBO9h;TlZq%w2T{y}IJ57^mP3;I@#Cl3`*2 zhCTdh0^la89@Bo?T5xnS4ldBDET zAfp>!VG`h*aJrmr8|nB-n? zD!f(*a32s9)7#PSQL**_baUBWhuDJj>)o?Ll~rU4DI&^}@me^N+1O%>>J&|-qq?#d z)#|WGk&>3eBC@__g>-BgBo`FVNfgQy*i??0gB$S;8;zNbxHDpn<`0Ze-$!40I=tGn z_k*-n1~z;>j?CEwg6zyG1O-tv*x1tpKpZkp6}fRuR$ryQy1c$1VwIbNqhrVKX;nr# z40!fk%S`aij5vC;RegUr!|yC16PX@O*kj2SjSqb}-m~AjA($K} z#c*t)0r`^h3x?9Ea)>c(xN{#w%6ocexEZF{nJPJ0aR3KDY~o9qG79*V`tJLm3$5Zc z%wK*>Oky4h6KyouB)g~T<|Ge5v6^TA>-NcAfi3T6N8QWSKUqx#;&w7F26D&Fw5Qce z5XY37n1Bh&Id_BWx{t?L-ZpUv^!HgS>xoN44?Y=MQmX~ae2|j@h)k*of>ag%Bk?;8 zeAMLza(=?g=&AoR@<#yzxyY7u05!@r)rB-qk`r;#c5sA&C%;w*;JDr)g!jTI_pCk} z#3>Dw41@HnnY|8{@`L!cJH-1?IybLKWZxoH{5T;Wj^Myf#WVqIZn~8#NbeqYwdrxiluU!=A)*ZV0Gfh9^?LG56pw(=M;la7&A{TT` zmnk*s$sJtK0G*?l71Yzm&uHBnpK@|+nZV@VPGI~xrYOfOq@DK<+A!;6J<%M*2+2Y6 zk4kIp+0(pfJrSB6S<+4>oU-gf%0#Ll%UhqzD#LHz}x}TFFk|Y`s6I?hDFg~ z77>>mTy5dN{sEFP-bEZ{`N!dnWZov1^PCyGI^}TeSFQEUb$w}kc(ig2T{|q$kodak zoett9s~=iv_MOdB6F5+6U9%9JcL3ie7C7ba<`*Ny7ia479{^|JHnubEi+(TE?g#%f znVlDx`3KI3jN12Mn|R+5b{L7~`RlW{SP(uH0pz zqY2E)31RZ^M`~B_*pG!y<}cX>Z<``GR}w`b~8>2IG4#m%dK82@GGr%(Fn0*qT! zXxfdyU}?Ofj@3JK>-ehY7}8<+1chgTYeS6BAbCZ6r$bmz>B+nWl5TR)G}4!xEH zHav~-;~gw>zN#T|kz$IZ4?Br}iWX;4w1>oSFCCF=MOkMMw~3Aj@)T|5gijWyTMgOF z28r?D9P~{R1`wVvR_CpAj;^f{|9I__^aOpwba}$0;VP5iW}%zIub@qQ+k8(W$J#5A zTZEp2NQrX%%@WzWaLe5KY~Hfg`blN(vL+Qet@ucjw;8wj&=9A>#f@URCDT> z9u`zJp=_-_&P(Ec&#~@jky|R4wAHXjIcV`NnihfeeMst`kIFagKc7j;S36fHRW>90idZ>fa(D@O_pjl}s@&;hg3edAGl%o}(4NjjWn$y~EN``UFTn(e?S( z36Q4)v-Cx9vqOE3V|;nD(e}I}2*Lre+XCF zgsw`SsV41TbOe*Pl_OVD@cYjJ2PYRaCGV+BP2TcNA)}FH3cl~Onf9fvzscm{e`K7p z?A4s}t)z=n<@wI9yOeD}c*Tv=wp6mh>4V_Bm+2Y9-36j;wsxYCSz0U`lGpG&Mli@{ zN?By88T2qKH^@fhjur)A+BqRJ7ZwB~h{jQ0+!~z>Bg6Ba1898o=7uG`^`{N(zQTan476Ek9TF4M)v`?w6U~)0@h|4Uqk(v;U*L+g6HH8 zn3@m`f|JFSy6dB3VyDYuse)gdMm$fMB8tB~dpu*;rKaC5I44=w!WPbGo2KSWLe+*b z7o0<;wPJ((F>D)*_?1b0?Pk}j8$Jbju(kbNT{x-OM0dg=szC+2C>tg1zZE5`^J2%} z8?|U09Bct1llb<~jLz)D%C98wR98pnTaV9|3e4>m(;F+v2p)8mXP57p!QLM}`M>Wr zZa+B}QncOhO}h%2_f-FLb7NM-IpQfgoPguEiDFiv&c+N9kvNQb|cYG5ZqF-oGNLD}D_uM=#I|tus{DjWZre zndI>ODuQwDBoCY0GpNbPE3q_ZWo3jXV@q4?`TNaAxEZRg1zV&>aa@k6FkKiAF3cw9 zrNUJH0jil5Qa;e`0ELaM{>-@LwCbfKYnr}u4^B?=;X&R9*_1ls9 zv_n$ZS@T$7N?&%O#qxxcL6B+vn>LB5tHVEQ(M~@x~B93-2mlhtUi`WD3i8 zEv;vCZa(gNFwp@jA+9i1%(Kt8eCSKONEDTfiog_tbbBV2a5I6hc4@ zi78Bu;awY+a)dW--ul2J6T%VCh7W(`~l zr?7lNeAT`?Z0+84L@z{rx~w~wQ2AA9!7yuVm&hh?9~XL6_Df6kFX(S&T*X;g>x);W z|I|-^ExczH(=&MEA7I@wLb@tnDTc`7UixSK#T{Fmni*@Us1au0E7t(b4omk5x7}9t zGa-ahEvHah{*UWC7cj~fIV?&(guqpWe(MzVbS==5FBTZhBooHF!r{^;Eqin~qx?ws z#)FB*P*j37G7{NU;aZc*)dx}L+G>$p)nEP4X6~5W5%36nzp+wQU^Be%F5-wI@HmRC zkz9P!Cm7nb-D=q_irpBilRjiVl|~x#H=Tx=j@3odve<1fOUkGBCe*T}9cCR75frW| z>_O;%c5|fu5AX+Kj)fA3F~LPVxI?-Ya%6B^QwQ63wU%IU<+7tZA_%B8v9bW#qHZZa z$U|3G>O$n$iWpHz#k+crQ8kB+ef4j)TW4eqsOh59o^P z-7n3Z&?)ei`yebWj?vlp1@-(RUgjjx2qBG2!DH5a9r>A_doCfrM zOJ;D^r%TK3S|LrVyZBlCM2_`l!W^3n#4UK2p5@}LmZikm%ae6WLU{?8ngY*`zMQtM zS_-d*`pYaDVlE#%C&dIk!rkxc5oZ;@26igsPw`?YUm42utS&}%Y3PFwA=5_;=e^J` zqQJ>PQ_?SL@jGNhXP)VbKfEz2*vttOqB@ucH;J!BlUl!gG88+s!V0wncwhHZg+dpw z@VEc_mMvuYZOg0b zWRbj=sp}MH@>yS`p$Wn{t~IR?*T{*wE{EjYc`#7=RXn+Tgj~3=+nw|hu{xFZ!D(Ws zUbn}Znvuw3M=X>2yMxuzk_-r!+~?FOXUq6A9P)6X`>(IAv5r0+I`C|qVkZ`3Y z(!E~ors>QI1D%gXAK=578l+=%?Sl8)wTG9sEe(W5+$aNGD8c9s5VQcjlEp8RTY4$= zX|8GCH@HeGkDt~omb@?fN0ouR1%8giWexMQSc9CwGTTz_PV?RQdaSA+tG=3GsNZ;Q zT25bFmUF9^CEQkF!shz${sD^fPKs212%mGX2g~5p2qOoY%dL4|l{@q<==Z%-9OmdW zO_+aTdZwPqN&Z`Ql$tqoXe5AuWzQ6x9;buL-z9Flky@NgO||K1Xt+r)58e3(DAS)I`;yWvZ;0#SZ{&P%qGBWDEXNU)Vu@1t6mb8S zZd<#mlXVEK6e-EKZZV64b5%6;z|cT7u&evC5;|SSRk=*h8*be(ny-P~$v31=qDd9& zPZrqU>w{8`>8!OW;O8X?%}p#m6dB%r^?3y(q)<4G(gt3^)MQmmZM_FAb}5JuxQPV& z`nc*-FLPD)g!VD)$&+LSz)&cfdR?A;^C?87`UBWTSKYgE?f#gm+`lfvaeUNe)BDi* zbm5!Sdr&0nNA!MFjRbUnJEHQktZ)ZsaUvrIjy3o6%FM`m0hR%qX*_?n|E-+OQ2BW( z)}c;sOhr3$a*K>q$KD*A0Wu9aTCHcUa51Mehx(h6-^IL}ln_KO6s?Pdk~|nx_qvR{ zUSlPpYNm$5HYpp6{HLc*emJF)AcAG+qLGEwkLgfK?1kIUUQL8wAsTZfW1`+-)kp^` z$-5%jg|%EOlLNmF9*Jhk6x7)a5q*p%I5%~=yeTH+KThA#1f1%}wN4OdOyG}MQ@+rf zipeyYL5Fyh9ZE?9w*^|Fl)-G=O0t`62}?`D^63e@%h8A?k!Q{6)(O4AuH|S|c?$Uq zoFwX^E7Dy^N%9P9UxoWZZhY%!<@t%I>)nnQyVOVRRO$NL+)Z{+bIyoqKwfK=0uF&; zZq?Jw7&=v+_qDiS1>G(AI`QdfY|)^sg(EvE{Pe7?>Nf2vNuaCzo(fsigF{s(ve5n? z0FWqvC@erm7p?8|>gr?a&f?V1FfIJ)BG~)CA$+g>N=0sw3|x#p8*zoRC5uL?s6x8aQlYTUb%RAA{xeJ=ykTumC2z`(Jf{xAzmBYz z5Y`>;l~fKqvk$WurOs5{9zsrR51!sxuMyU~ED(Z(zLEF5jQ`{?&q8-i~YUV#)6F7%U`ayy^K~J_=$6|HMg3uJ$a%ToU zuFpfjeTj{X)z3Q^f96O-2GuU72J6w|j1>a2E`<~g&)ENo^QiYNI}_Wdd-L!1LZ#N{ zzXZW%*?I2u->NxT1Gq!t!^ZsGv%X%;G#$uBBq`X&0W?VuuCCCUKUqm{Df5WP|8&3} z$}r7v+s;t(UWhXQMj&J~fpiYa6paNAG?!qW_?ZE_t7rif8A|s z&pTXGO#5!f4$+|Ib7th6Yu&BcnyuHUqA*!Q+aRn#DVl+Fq_nW)YHkkwHYLI@mNIFO zjOvs(=dv^IqwSny&5PzZtx~Kw=5|#yH(~i@d@L#QxWi%+SemM_3`e=DX zy0U0+<@?TMfPw`&pOgFt?@11|#}Z^4GUBtuKv0b<+y1=J1wIee^8_Vlt!XcN(_nW0 znVazoh^?HiInsQralmL}%QD*ajedtx0nEI!H<$inca#hE|F?sHSL}j7I|}-@w~pNr^iyL6J>%zm75a?FzP#aF|3R$JnsM4#o5DMCNbxJHiFw zVOlWBRj%mbI9xfgoyq#o)+weZy<6)PGBVE@h^WDY_w4uFg36rQ!AK~uon7TJt0L>q zlH7mpd`~42aWdsTlY9yKaVx&b&)#+)GBR8l8tJAWCDaNSDU5)=*3eB#C(lP)`StB{ zj0I9b+>EP#0P0y*vpAc?-URG56Uu*pojMJIB&!0#`d_aO?=?5};=@~ITQ{}#XjE{; zSZ6=vd}7-PQ+u2*MIS`A^)H^=3DR8OLC`crHvmS zRZ9aeX`3rOA-0ow4pI*A;SKiU!Kc-2SqLZGCg2oi!z*$Rt37q@f3p3Q0vomNjzi*E zg0;oGmqsi6G9g1*s{+IvWy*b=zszF*;kf2!0K9TLt-&DN+NoK=jUNnd92r@yYDkzA zem)kh5Af#iZ$$Y|Zx)7lSa8Z!oaDe*CptS2R3~F19*=3BZ*1~Bto84ovMsBsn#CAYB^_<-lS828|1;v@^rf~ zr$lC4^Q%c|>(|M@e>XLRbLmd_m#NRuLH7@{(z9F*^r?Ma3BvJnh=VAE>nihl*)hc% z@qPkqz74P{3}cPT|8eH&EdMkqfG)V@<76v2BAdiO`Q=Ex zntKWo2~2$PHW%`2^Q{eF5O1mt1x14@4;~L(mS|CZQO(w>*6Vi)h$9_qB|x&f8m8MK zC+Jyt&e{ykvg%&IZ4f}zv0~=yp(*{yZ_Y=k`_Q`eS9`La9NVfxj5QMv(WGzdnc@bX zYTyvAC5+(m(M{Z|02LM=Yx>L~(N*pMbW*{!#ObRi+cBDNJw^o6TdfnNTTPX#+a%xL zB+$yCyswz74J%wBx~#g0jTJ@nHEKG86}kDW4`nJImm96^a~^$WM|4tOb|QcmH%f0PZRXv5Y%}^FWv5me5w#e=L8Wa{%icKTzIs zcIw_W_aERZ#pJ&5h}u0p-$=Va%9cYL&u|+u_M^K2-)e%> z2g1idPD{07hw%OCCVETUajLwI-s_0_C|5oEZrs838;cZ+(@CI%>E|21*bk$&`;4t> z$=7K5vN_9dk7uOqO1zPl+{7YE+dggZwc4k$)-INehX}95dV#z(2WywSyh*yT--_8J zw>v%~QN_3kycs0X9DL)tgfW1qpwc_J#BQ*E^OqgVfinyh55+W$;#A7>3Km~#OLlM5 zP8;#(r(+l@1jz1DMWNhans(_!o(-08#1;%g`4j9SiOBbP<{g3HMovxk?>S6y^8W~; zxtpJMQ4-3yDHZ-hwj!ndVgVKPQyD*3mGNd;G`#P_cqX_}v|O&z(ctbgQ%>O%5J7-6 z_{?A7`lt{Xa+#IiI;j*b&TT=T@Z`&Ocw|TD-mtg)fQ3&ziY9qGZw(HIW|Bz`Y*TbW z1TRY$Z(!Im>DGo7fy(qwVhWaJSlbP|Tyo{FTKmDEbqR-E*YeuEu1|j^m9anD5G-}ID2DUP)UB`qq+$mL6U#{6Ctb9RXE6V^S zi~W!@A^oIwEN%adqSUNiV$`Mc{>-Q*?>7CDj}HBGSq@h&EiY#~Hom|Yp9GeE)5fNn z+koO#J=O#x(&QD!zaB_+XyR9Z#O%TR)0xadWz*{zFS9Ulq;HPs`A*&AQ^`LpT-QmZ z&v$)xx>;(QPx}f@eS4a7^Pr0^VO@{5brdl!?ZC<0iPl&4L}w{Gjqc3}eEaFKgLv(n zh64Aqzod9kQZE{dinP8b&zkMKpv!v-KDSPb2aO2$IUnee5C*|*oCHYn)tfJRd04(l zy|c>aOzm8Yk`&s8g`DOmjv3p;JMhAk#X>oPPePyK5FlU~HHOI_e#HAYuA z=0Rx*l07Ahodg@gxg7zB)VnvLel5-VUwuB+CewjplhmWn14dcKc;7B5Wv8;6gm~$A zIL*`1w3ref854?di|BRD*hzf)l-TU9+T#e5gNxh3d5`#5e0Z~@l8xC-)C8P#8+>yK zmc0hXhW2AeFb*`8or(7o?FIAkxRK6sm z2bec>E?%A2!hk++WUh5K5Kfy?P7sUaL=1(apEz;rO;kln4$vVBSm2-=`v<0N(`GC# z{%TR}d7zO)9>#qi-(8tjGVh(;wIn3{2V=>QiG{8 z6HRD4Jb9n|MSm!%Yr z8pvx>AeWX%QfLBaSQmP`A1Y(t_F0tD;gnFm>ULbElz?#fMd9|0{69eM_Gk7w!?Ca;`3omsZF8x}UaUhcCO+9l~- zO0W~aZj&kExqzR{VfEkobt7?$(Pd{h!ml#5845H5ZsBxhe?RL#=n^P2o$ZC?$A2V^ z=_v+*-UPLuN~1bSq7zEDIeNGfxSR+IKst5msguG9^l_;S7>*T1+-GcU<+eqYMVdFMLb?qXc(p?%{-k3nww=GJ-OHx-W@^ zzp#XA<+*!YfyUe9O%zZ60DX-|3>q4BR;`h28?m=r!Yg!B)(}l-0?8)9Wa%f@csVlE z;jUb)0d^N@JkwDZL5dP4@x2(Ss=a&v-__#qkU;6t)(p2^t`oJ`BWVKmNu-BN`Jg!H zBCuk|AS|Q^4z`Xv6C0KbNby_R5nC3^Gj3~B`SsOhV7m}EqLY~16NQo+1}`&1d?C}% zkwgq9zd6tA$^761&06yY&9LVsS9uah7?xUaA&ZmrdAwJW5ev0kFf`ILP`>`w1P)#0 zWCT#O-}ZM=p#LnQj|bN`crNhPFfJ}VpMcGx312)ILfd6@n1em9y{tqBkc{b(i7qfj zF85#>1R1cTkYZWNbI%-tG33u5am8sO`ujXZJ7S6JhaP^>NgDS< z5AXeIY`wqQ)yU?tg+y~mdfEBBgt!*Mv%E<+_L()jd}C#oaK7%e$rsR7@aoF-3G5xH z(`h?jBr~9IjcuvD7u@ujrhd#RSXV~5-<(2GOpJ9_LjP5G?x!dWffLcpxm)G$WPMj} zEaiC#(su}WEi*lBwt3b`^p%Bbh!<0AU5&CJesAVCG{f~*3;~rw^t6JMNYP>6Hy=)lmqEtuM2<)U9Rc38Mt zvS_mb5GOeH>zF0uO!Nm@_!+igWrDgJZ&;o)xuboHi8c56Jq`y6MG&v0d?vUdMb44T zE`Do8aB%=+ngGqpWJ#{|&U(Uxf*tA}!xfclDm{((7{4(}F=K#%(I&C$eS*E(b<>Ky zhwjqmmR>m3jER(zS(4dX@N;6N`ztNXW9e&iw;hKK35v1uV<$m~qPfsMs;rmqK<<27 zoP}Iq-wutBX>4Dms={G(>FC0OSN;Rf%%)!cMaq^i-%kbxx(Xwi(@hWFF-4a%o2alA z9g8SwjPo#KMqDKDKfs$6copEPOy}s3jUlSPG}z5>@715ztD(XQlK^{hj${?;wWEXcBLhc2&a$LE5N z``MM7=&~|VjVCYf++=ak#8F$@p-U~?$b*e@UZZ@7kUnOj@wMzv0hcwKm7cku1AF*M zz@}MEz@qI6_8QY1YpxHh=~E^cNZpj2i;Gd@?R}N`bIA*&$sQWXP+_rDwjn0gQU5bQ z2GZp&V9#)v#e*VxLFJ3;Z*8lZcp4QUlXF=L+kSQtLub}SHq5YDhjBVFZUE=NF{joc zFUx}fT~mE?s)BQFv7Q1kLj`)_7>ZlL5Zn9|8HWx0=g4}QYB`y{Rob>--$wDLgv_Lx zES5Cu?0CuVucF|%DcdDuhfB}m=d5(IkC()zdO-ZoePqY9i8_!Gwo z&me2%wwxJ4^ezveONpt1dO<=FT@Z$Y)Cm!S#=U~x+{~)4dV05P9sm z8quC&Gp`M$Z}^^qXmoi;$i?I996v>}laJ=YqO8_bdG@NhAhUicbfIvms9)e}pZo5w zei?oI?|6qdwvjpmBu;oK%8Kwt20@5(to-|>%}jp6(NHI2jZm6;D?ULB0h2=Su;pbB zOTl9o@0rR3osD4fvdNbIF9P6*6z9fzE@hF}brGBpgQS?H8-Lo5_;*dN9$cT}ryS;i zKR1gE00?1m(i8n3GuIwz_WgA)WN25jxE>efJDe}fd@v0z*PV>4uwqrNuU9noDgzNf znq-QJwx$&G+28$m)VP>qMt-)EI~qFnF(XHVec$*-&IM=;Ox&n9cVbo3wmvpg_ObhR z<`HXIU^n%No^xFd90VQc^W8WX(^!*YcQ?gKdQb}at=F!_kD03cjda*bPfuBE$c#S! zG|h)Zk0;5OLFhLoD6ltTvOA-0+YX-e6$bAK8;wR*4jNX2$%76iFi9bz-q%|(koXojqPlR%oIkSU-tyV< z?4i6&=}$SE*0iv@DN5OiD*ZnKLo>Y0b4U-IK0W9%4~Y=!2^3N$rEeRAQ?$FG2*t;6 z0L~BI$*v;OY1tUuUfeSrMu|8Cs{%mS2S7$Tl6rbqxO{riMy>GD%IRQ|Np$^2HuDif z2$9CtXV35sGtU*^8g=BiHrDqI0>&qs4$wx@h7OOcx_cyh3dw9z=$J_zPvSt=ON>o}5*5Xx{7rFt@u# zCTK1K`H?Bl9DUP)xKxrsZ#zOEf8NHb6frxUcN2_fI3xV=TTH&$ zn#=JwRgT=+>0S`lrj15K=FOD~=Yy8P$2FX%#(p52OD3NclDe1Qe{dJdkNd?}Bq`4x zy|Z0zt7&u5gH0m2U}PB^e)iHmKs`HEJ5N5@%SdDdv0|>@)Pmbj8NkiZz8d z&1p+Qr~D!wDYushbc@D?L(a)?K~Q>b1Yt?f-6uY{ITfL&!Q%}yM)LS}=x<%I%M&A` zDLfE!*FAo<&_SxYNoitWS)hch!VCbiNW+$32Owu3OyjL}dLpKwsa;8^G?FxqWdtuJ zal!NhH~^yH3#HK9+RFTVrD!|LnIou9$&~~FvgT{Yp`)BqR zs~?sNk2`6?p1|h}dV8Ao%ZPr>sotfjMsqAy=^${y307>YDLn@`6k1r>J~`VHSqU+f z48w5*@^Vkpnq2-uv@Ls{AA4is+vyF!@cgjA%s0z%B1WAs005luIjU25KgB*w!fTxt z#(2PymP>{wX&fF0Ds%USK=12bt*JX{+T?=TF(gWl46u=vVUx8;?ip}F>Nx3Kth%hT z>7Qml>g}-51|XRCoU&)}2OR+?9cq-`)(O#rS8U)DRPnEdrFWA;l5rbsm2D*x1wDyg z4hZOa8rOs3UFFR2+v=Ve)%5m>m3-N)N+O@(1;#+@$JVS)w-Q_|iM_ze?dND-0*rS7 zw+wd26|bdPP9TjA=#fDZspU!gy+67$&!suI+U*0 z=^fRcMQr@%Io-~B=ac-wrdzZ|=tdo`u8;3-BDM>K3`q=B{{RmgdR5xyGIkq$X1P{^ z+IgjlX!fiTsPc%xW4Ine6T!hFJ$hHM{?A%FTWR{S-;lM4|)sg5jsQjKo|y$l%~$5I|Bn+us%SPr~gW=zj&gF{ZV&_OhEXbu>2v z60EZmBX1p#&C{>~x*)8NFBv^8-0fpMD#T~h)kG%(tj2y{@U1R+wk;{+6)NxnAC*9- zgHkRw(1uu3f(L4qNXI6jQ_vcbdVZBiM8J*?MLRg@)6mp-`9(Y*n;nfY3%JoqMF4;Q z(EBqya1K7S#yRcVy(#;+%`~5zwkwnd9=*A!nDRa9MmWbz=Ak_E?@}@%a1LrFIb+AQ zO5EgqDi-fajD?SK0H6?l=qA(Ek7` z`6@fH7lrNIUB_mSOk9nfIO~@c@{QC? zb!A45GazPY<9LHB$$~j20eJbh5P@FAOcP@!|Pg5iB=`Kww0P`l<$$)wh8;opQbs^dJfexj)!$QT1f8n`P#@M z8^JV%P)8(^WulWD?d(Sx1o{fnf@?|iMuOT+(>51+WXKOySvklDIoJUE*zaC@XQ@Px zU0qu%K%qe^w|;TS{{VR8a(zLrzfNglju;;9Fy$4z$*|)s*MJ5?5_N^pNz`f8Sg62RLLncXLgOi-_N2grZYxbmyPq9eW z-!I8>BXC&*FUkgbA4A&|C z7#0}=rhkBR{(`aY{uF4lTNy6xqicx3Nf{7t4U%^@PEH0+dXRcn(UfJoDdH+6WRavi zYvE`lhBK?Dkqm_+DS_*p?Hr%zX(REUg|2+K+fu#t*3ZO+6^`f*ie$N`6pl~SObr{-xwVFOLge*meExUribv-)!X0@iYjtif& zm}H0s4L6sCB?luU@rF6~s7=$}LdqnvTZLAb30!1?qyPZ}>0H*Kcn+dL9&N;^3QM;E8y!IGIORv{R~2&`rKugk zX(SLwC`jD1Ia0fz`L}fLy$?>khHEnMtm6rJJ?s#w+-?`nsyw0`?LoIW2j(O&KoD7CvFKOWR6cY z)T3mNK61NvE>8Y-o1|Jwu}Jbt7pH+KPWzf(2DyrNR&_E-7;`;B(jCG{{R45X{*@b z#l_k(eN9B^(A9|k=>A5lA>eaU$M;29z*%0Hsgv&Y6$1Ut`&7z)U&4e0>w}CMkxv|+ z)e!0`QQzxSCP)u|z|;Ei+*Ex*$JU-XAcIsPa(!r{zgj2(hlBW2I@8JHk`pq z0}1Ex6%jlP)Q6`XYBuT5ts$ZoVh0rqXK|^GLQN(z7Qi1$uE!vBso&|`Rd(cz)B-qP ziu;elca2E-?&HYy#!Y?0 zroMae4Y88d+9p(W&Q*v|!x+Im>z;D8M0;2mUV}NQWlO^;NG@)!?&pyuw*v%9F}+tk z$mIaed-SL2uW2>y&4!t4GvIM_LdzpNa>2$il5##@?(vGuxieZMlik@XM>f@+9Bm9& zpdHn*oF4i2t0q}4Zw369%{tvT1%hvsu*b@v?%KEjAQ`}}w3L;}zbmsfG~0|`;_72- zI$?Io`x%guGsbh04+Eh3X1Y@Z%dYv5-A8lwaE4_LtYQnu+RgWdIR}%0k=D6L7TViW z7Y#MaLWC@LHf*n#;oE2g`t;|4+Pf_#818P9N187oB#+HyN6JRdNmWz)UAP@Hfzr6@ z=+8!r=0>%Y*3ei1ZX<6oi^lEKL6$Bp^wFf`j-u9*PJj zuNB7FYK^ABXd#KCVIX+PL$Qj3hrk>m$s-4$;<`;UQS(j2@e6CY+iapRa~nSVsRZK% zeF)?V!LFx5I*Hd|MYwYs1l|xZ!Qd5UBezq>VeL?{isC8cxbmYhMZHVOw=dKIp1z*E z_O4v&pSj+xExOHg(ie~t(d|DtAoH}5k&Zd*RcUtE$T_DxPg$p!iS0+lFP^Uhe4j5&MI4dM$Fqx1jz0FrO+L#89m56AD6$k zHI}y1-d@3V730riA$W?(3-4J+3IdUxm;iur!OcMXt!!tzyuN?4&npW^(l%_y7=gb7 zlacbV802$TVRI`TjK&K~nPG)uFewBukd-TpU=jTfesNLVDP1DyEUhF+IA&lPF~DAa zxfvZuu1*TRTLFiwsA}g<)jrW}HKI)%Xcjp^ATHblPyx;{jPNo(wa$izRr?*Aq^k&%$n#}W z`>+|0JOPuFf;ybgyOPYfE#$ZRR982ULn=nB(JKT{ssL8X0txN4c*yC=u5wnE<53p& zF4sm)uOyLTO{_s9J&r&>L!V4nQK?L=HNe?07G!N`$YO}=fbrvoVU+=K#zk^JXSI1| znM{HyKY0|gvb#*n!)*ZMx36$VO6a7n^*QUlR5J0b?=`usTTi+BN~mjpBWRN3o*U)B z8%Z4pBX2=SWJyAZWq9tcW0nGq^B_}!BNL1j&&sXT^O02^5h{nZCOdh&bMQ}Yw z^CV~#t~lUe5$)Q(qVRh&d_K@iV4txfoO@(f&3YsT7@|jSHcXww_vbtxPfGePz;c;> z8|eQ4?8fo_PQtkbc{SCU*3xm!POr zWDFXadI|uUPCzHMNWDJ_iFiSS&T3JS>)xnLcsK&29sac#Cp}MEcw>y5(?MZ!Xrm)N zXr>kuqVj4c>rx(qnB7e#1Z+NGQ68eDZ@u``UYybdMtYuV7Ub|TQy#s4T4F&g@&t`Z zCjyq^D!Y8y!1`1dt!t)fji~C^w%UEF{{YKNhYAnVKhnBrY%J{3ON*Ba3@Bb%pMZc2 zvHS&mUE{wP>pv3wNhY&>x-C5^F7rmd+f$mzmirHGZ5%X7Z* zkB|I6<0(?Z!>w^OzMUrNFC|@xD=@|ocN}#!=Q@lYb1F!gE1Yqh=bl9`hAn=`m*^Ys zIKV!_wqdpVWx!=pt=DlJ{XPDb=T3K(&!M43QI8@#%UTh^dv|SfEYe6Y?~E!A+$r_- zu5vd1%b3TQ=C{2C=7{m;Fd4>r?%)of9CKcs;|(SVuC1CeThZBLvbQcYLQ+-vi|MLGPI5ceoz!Dpy|di zE27h1Q+Z}9E84qAUvCYACI$iv>c$PMuniN=G1tC1u90nxufCfin z#dfy0HdijX#guUg3baoq&J2R@ZvW?)hiX`4z zGj3PRGMFDbT}P{Q1a>@B_WFa_*Z3>;EcRP+x100Oj708)mhG{33 z8=<#+E%Q4Zf*npqLl(|4&JU$&L?VXDOKXeC6V7k5tG*T1Cm%G5akqBt0pGQ7xZ88R zR7{o$LB746qJbo34;T)|=4>g9GUpf|0z2gTRoL}YCFR}c_JYB45LiCJwOy>E8C)}D zuQ(v&bzzZMYZdesGenUu_Q6aad8AHre*~crqFtjFfs`km+wD<11#kedaH&5(JFENzlq?*xcQ47vNDfOji#k%QD! z7m{0D={FV*gjwCGfo=X)6d+&1kzgUJK8e)XSo05JKn?YEuoJj6(*;aCj3nCEvVBzj|| zGWt_>Y`3t?z_ea;%WSz=<;FITRVlEIy>pt+kIjQl^C7uuA1bms94smT199DhxDYdu zoxGY#J&JV_+=BJ>KkWqF6Wun}S$viO9I-r*y)bjh^%$;d`a3&R0`54L7gq9ORBzr5 z+{WRQ1!2^XayuMgoh$3xJti5iO{8M-?U<@X5Lcbk1DC$|-%q`HSORc%>_>ND+HR&b;V z<`I^`Y!UfXiEhlhRR}o2CalK_DZ`#hvRTMKi6_`^NrhrrEgZA6}J+9jhhoIT-FLgiw#PN`PUT2P3!E zwk>1w(=j$34s%?OW6*lGXKPwrwfHgJM6#}OsyG-uYtJ>!83P-$3y~9?zQLG}Opjte zI`!$J{npnTker6}HI;p&t;l0Fy2uM;3~}s5I8DWbl9E1uywhf~)MIZj5~?yH8`R)q z=Er|-qM2^8X}9KmHhAE4K&=_WEZ89JanPZ`$?7Z8yhEgUZVZs;bB)c62KDElKIXVv zts(5?ZN(WwH_XFs&qL@tV-@JruYJxMv@B{z;r%H zC5f-s`+HB8IHr|+*sUU21ZsI@#xgU{2dfZCtIOl7dl;s*p4FKqhE+wqNkI{?D5w-+ zcjKWM2aZP~g-@{#Z>l;|s!2Vpwva=s1u=mnMH}aQf{_An$_VF<`R&azeNOV})od?j zx>(gjE#>FT%7pU)Lx7m*$ExSObHm0~Y4*FBZmvY{Ie6^FxoGY}jet1g7*2%u1ZJt* z_@7I&f*CAJDFAR{(2lh-{f5&UbXYZ|1p z-a#YS`O_H%jB-m9o0*vyD{vDyJwYJwy=w~N#TQK*HI<7IBW2weh z0~DM)u_?ZY>&?lNO_uIi8p_5mGC1TINd$2|(A?v46a<1YFh+5j!M*WR^20T@nQvh1 zShLDxVHV&D24DHA1uQN_S zNixOwafAFI^#jwjUeokbEy_zGqN0*~wcum7CxAWczwq{qCAEqCfK;v+l;N;WK+jL> zSyiuXjp-g0LctaNEBLW z%Wn#Z;}OOaZZW_B@GD6X))3JEii70${{ZXPpE83F=t^KdG;pFRcS;&9yhlA{fwPx%qMW*VLL-qS*L% zPt(reZS7)&=h*;1%Db}3Idfmj^*o&J%|pJwp-%GABy#JV=O5Hn7Pn>ObBf=V4=}qz zdy1_r2b`mB?~3&~Q{3=wV}L=y2R^2ry+04@RwP9SY0pme8H5rT8iz@A9mQW`+MF|r zjI4?N)_tkVBIgWo>rmp*Ty+$i*ZabXL%AYBkOCpkek#gYO6~Ik2cYJzk0vC@48#4J zVqLQwDu|c$KaF(~Dpe{wjaJp9aa^{DdMkNNd`H;r;_M*~u zB5OyI+C?L}62H>EoE*ZZZb;(3eE5@QG=GYhYqx9~fJ@ZROrMp<<^lX`%*?5CK~J~p zdihODRFpff$lxr%ePZF6V;}$mde+P^?o1#I4?;V7X0R+AHn(@q6=d6y+r4!5@w(#- zK_~O~uQFOA+PJOo;d!0Fiu(=u7FsFh@ILNM*RkJx# zT@DKJ%3}*%nPHYVl(f%p`^ea1jHu_oL*BEV(or;#wWRVhg2Z4kTy^89X)I_CuO zNgci2#j54b`M}KOwywfDf#1{CtDIiTQ<(A@Ws+C5l>!a2A&eYjgOpx<@#)gF;nU}~ zQylj&#>`IRaM&!Q^ikK;bJL}1+G)ZY*yD}ij^OdSJeD27&rm&nwWl4ROZB$5R&(-#;CCLL)!A6symsNFC^n2L9=(4`eXWQVb&vBksU5omnVb!)xwF9h zee0G|G}wz^cuJ}fA0P$kPZrE!WK{tN9;Y>I5@aaMq#lR{DG_BcqOKGVn;i)?oyly@ zo-v%duV1_0=~*_wN8)x-wU-OqKb37<#=#42JPy8<&)Y~B#iMorDZ7#B#a`)&Jx@XK z#fa4WU!v*2h7EKkla4kg&HV*^54@2hu>>B2Kb3f|!HX}p_={84WKz*tL@guqGC$1N z`T##V_K7edUNB91*>yfjSMGQjrA~U>y^$L+Ra|2%Ngss*;zj$xUyhyWB_F-pz}Num z_?nDh3}=&Gf#x!N+R8w6^3T(XicL8f7LNr-bur=3RG!^7lexBfqX1C z%4*gsVqySbMt)xY;<=ZFq0D6mmggf4f!Doy9p$WZ!SX8(rv{KVdRZ1 zN0+qn(gA=!ty_4dgp(dO5!tYF^%SsMNhF7IhRMgw*w5$Qi-C-qRBnwNNU7!@o@F3A zE_)uJR)^RyqYd{-Y#)>#q3>F;K&da8A&m2djZlz%PZc{_ypsWNKvWxuJdeVa!Pyw` zK=%bppeVd3CzD-eg_lI*3{zU`Bv|gN57) zt1`lEXGAIxFd&dPC+qzx#4?CjqbAa$KQG;Hf2C?^a|(NFav6r@NWm=IakLIi7LeLW z40A^!Op+*Q-4rlk>zd!iw9#!iZ!;>xVF32W9cnlh&dLa)wvISbKapZp;Xv#?Dcmp6 zqY}sgk~9M&0o(-ucl;?$tRa>;C08fr+{YLmn`-Q=vO6LscAS=OgV=p(mUho|A(Tg) zIKgGe$Je=}*st8XXAnsjjikdiwtWO0on> z6^n-3&;gy*lXoGpm~cpe6?Y6|=Quvys*LW!MNty`qdW}$b$ywGm5B(z=ApE94MMC|+0!b*yE8Q@z_A!2<){tWOw0lk*Y(04&$F zRg9%8v!B#9M;wKl%8fy1mHHa>KZJf0Z6Cw3YxnUo>N>ClE03Be2l}-j_iwy@qPgz{ z_(XV{RvMMC(<_V=m)h;D|u1*Yxjuc`c-}0k+|2Wc`R=sPec5u!N*WB?@7n$ zMlx}@&>-i!=iE|^93GwNGI5@Sno-FfqxGO@9dXV(({qK%Cm&jvWTxZRnYSYt8TX(p zL%4sFMMz^gITTP9CsiSGPZcH!0~kKk-qe^17uIW!ElpyT#pSUwN7Dn5k6MRLn+!=!q-2colkHx6)b=-5 zG|Hl>CME|Qp1Aa=WsW%%D-7rEx20N)JH}rMc)=YDQ&^OXZo{|_OpJOOfhJ9y%Uo4hDeq8nRA6n=X$jC@yss;xc?Nsk=$X_v#gN_2XN~Fq+x)@lR zNET~_kTU?q9EI}Fp~reb=Eo57Ad%IGR*f)n4}AK1)#tSn6A@C!y8*!bsYC)dWsESu z&QDhQRb0Mdu~>;>5fo_`c3TIits8q$g;hKCAGb-pQpuZZ307Y5`>Br7yu5!mv@#t$N8jggVKYPK4kc3BjrKbqGn?G zEs{?ry;P4dYn=V=r1Orn&~d>y;+GgX=RWkCiRcGB@+peK^&L+%V;MV#(-d{dAXB;k z0L=riiZXs-^fe-;4t>2SP&gu<22^B!N&pBuKo}mqsf@oiK^V;?xj1-Sk!TQp4^~NXzp1-9g z1fiB^F9UgVj#@VF{{YtarzD%4hXy%EzX$16nFD}W5Ww)u)qa%oIM^2La-F78)9O2Y zYIQ?7FBJSavesmK-7e|0%|n*qa}2rby$2&cqP))gLh%=ecE#ciCP4~+tG~6((4VOT zEB^ojuYUdHYBrH9N0lJw@--ql5<<4ZdV|OR0Is=e;OW%YW_HoXRHV6HtNQAAZKJI5 zEU`$ksmCaHXX#d^wk0rR+k?=KgnQSgUU)yl_l(lEp0=|{a%HwYQ76{}gZWk+*MMin zEOmmw0(RX;l6^T`R|N9XJoHv7XD%8h}Tiar4U0Cd+g!_-^Fow2P- zTB)zR)UwkX%Rs0w$Bx;m_jVt<-ec*W2PZYF{gto6R2>IY$osj3oc%FT%cA&><_Uk| zp4AsQ7H9P)M!5r{9kS{eIA_vU^f=H^GNpjM_OwQR$E1c>(YwWYwsaQ3dAr= z;AaA}H5sC}gtYUb7T^XrC)*yi=@#AqPyp05iI@ZTZO})@rcO<7Y5p3~G|3~L&rOfd z0|I$IcLVBreihSCE~zhzLyB31BeuWS_0aK+Gr~S9@ez;vJ5B!2(}Qjont(Cy9;%;t zzd`R_so{SE>7E*mWmzS^zT~~#z!?PfC_jW(O7bXTa?akzKdnaG#9nt;VF$U!f5g|J zM+;7tt5$JW#?-30UW>?gm`m)pUG3e^N?>$?LaN?v#y(~zg!=k@Dl;p(?TK36Bm7wT z*ndGt6%hib%D&xep&WveNzQV|t9sK(=bCrob4h`oNvjavl}Jurck5 zZzN|VPy*+klv8o&~U7j+gew{@Se})b!wT zZ|%SD>i+7{zUj<8V^hJaoX&zu1)+obsnSkKR!P)NW9oLD=(Y= z&IlN8IvUKpfo(6Pv`dwkM%#CwAQRsd0p6WUPX7R(`)~XDzvD`E9XtMl7P!Y4m4C*$ zDD;@;v9gtB5eJ4zrt#T=g@vM>wOvzv|L4TbcQ9f`%E_ja8frY$r#V5#yZdk zRsE%>ANhz{azE#){{W34)U@Hx+wD$2>8k$#jdF)T*wZ|^m9%g~B4H^ELo9&f01Wo3 z$)=cmPY#!Iz>l=7FR=9mfH?dO0Cr#6I(BjWp=tjBe^!s}EjTd$08h08*Un$@tSjvf z#jOw6Q5N7_Br37p3BlY*%V2!GV>@SWTb8#L%)C4`c+Zh}3au_O`5z&InVD*@3h z{e&&P4N}%3c`4?pL-iT{RWJ7Dm=_lpR;lYGa;q=p)K@EIp+|FnacgaH73+PI&V`|D zeA|>^v&ial4P{-xEpMc^NmgMQ+Fbzvk=GgbrC>ciCJvdmnIvEKSQ=gIIAr3hJaM}c z@rFL2V2W~=T!fxM>`viNP%HkM@YA zsLMs-{{Wtg>qs6vH}4l8TBc;1wX7fa^#1^bFPSz@Ev^3m@9F;l3P4;f83PVJlo=3b zXeaa)R7o-C%7K3tG`r=`-;ICWPw}Uyi#wf;6*J$~nJkf^{{TpxP-pJvC-4KBg@Kd( zY_hoS3vC~j2#A;np)=?y>H?dWVg8Q*LH+rMKV74d_|#%D(urhqEB^p_`+WyNQe%(1 z+Kg~|52Y3XxzACYoYR2AewY+vZg5W>s0vS~<3I`na&TzD#xe$a(&MgJW9vZ9J-?MO z6+;1@quz`*LB}*_<=S({T5!lY1dj9o+>*HG6o-MHN3}Tr0C*hYlP7WQp0og?AaT#N zC>_bqw|YU2{L_y-^Ys(}9yuRgw49O;9G+=-?sN5|JGT$JiU4L!6cf)%CFovk28lSkoZkdG#Ih)X_x%M>el&JUm>iYNj#)@O?9TZ>pNt&EWQ8(~7BMnTBuImqfss`s~&-``1f zBF2v<3wdJzoN|7&Q9vG$bDp`RKAFg(iU2dlDGB^&qJR@TV?5BL?L5&%E}$+?v8B&F zD597E>C}EyxFipniYNfwaCx9(smIcaC;-pX@}(I5Dkz`kYnTk literal 0 HcmV?d00001